>> theCube presents Dell Technologies World, brought to you by Dell. >> Hi everyone, welcome back to Dell Technologies World 2022. You're watching theCube's coverage of this, three-day coverage wall to wall. My name is David Vellante John Furrier's here, Lisa Martin, David Nicholson. Talk of the town here is data. And one of the big announcements at the show is Snowflake and Dell partnering up, building ecosystems. Snowflake reaching into on-prem, allowing customers to actually access the Snowflake Data Cloud without moving the data or if they want to move the data they can. This is really one of the hotter announcements of the show. Martin Glynn is here, he's the Senior Director of Storage Product Management at Dell Technologies. And Clark Patterson, he's the Head of Product Marketing for Snowflake. Guys, welcome. >> Thanks for having us. >> So a lot of buzz around this and, you know, Clark, you and I have talked about the need to really extend your data vision. And this really is the first step ever you've taken on-prem. Explain the motivation for this from your customer's perspective. >> Yeah. I mean, if you step back and think about Snowflake's vision and our mission of mobilizing the world's data, it's all around trying to break down silos for however customers define what a silo is, right? So we've had a lot of success breaking down silos from a workload perspective where we've expanded the platform to be data warehousing, and data engineering, and machine learning, and data science, and all the kind of compute intensive ways that people work with us. We've also had a lot of success in our sharing capabilities and how we're breaking down silos of organizations, right? So I can share data more seamlessly within my team, I can do it across totally disparate organizations, and break down silos that way. So this partnership is really like the next leg of the stool, so to speak, where we're breaking down the silos of the the data and where the data lives ultimately, right? So up until this point, Cloud, all focus there, and now we have this opportunity with Dell to expand that and into on-premises world and people can bring all those data sets together. >> And the data target for this Martin, is Dell ECS, right? Your object store, and it's got S3 compatibility. Explain that. >> Yeah, we've actually got sort of two flavors. We'll start with ECS, which is our turnkey object storage solution. Object storage offers sort of the ultimate in flexibility, you know, potential performance, ease of use, right? Which is why it fits so well with Snowflake's mission for sort of unlocking, you know, the data within the data center. So we'll offer it to begin with ECS, and then we also recently announced our software defined object scale solution. So add even more flexibility there. >> Okay. And the clock, the way it works is I can now access non-native Snowflake data using what? Materialized views, external tables, how does that work? >> Some combination of all the above. So we've had in Snowflake a capability called external tables which we refer to, it goes hand in hand with this notion of external stages. Basically through the combination of those two capabilities, it's a metadata layer on data wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud up until this point. So it's effectively an extension of that functionality into the Dell on-premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake so that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> Okay. So for a while you've allowed non-native Snowflake data but it had to be in the Cloud. >> Correct. >> It was the first time it's on-prem, >> that's correct >> that's the innovation here. Okay. And if I want to bring it into the Cloud, can I? >> Yeah, the connection here will help in a migration sense as well, right? So that's the good thing is, it's really giving the user the choice. So we are integrating together as partners to make connection as seamless as possible. And then the end user will say like, look I've got data that needs to live on-premises, for whatever reasons, data sovereignty whatever they decide. And they can keep it there and still do the analytics in another place. But if there's a need and a desire to use this as an opportunity to migrate some of that data to Cloud, that connection between our two platforms will make that easier. >> Well, Michael always says, "Hey, it's customer choice, we're flexible." So you're cool with that? That's been the mission since we kind of came together, right? Is if our customers needed to stay in their data center, if that makes more sense from a cost perspective or, you know, a data gravity perspective, then they can do that. But we also want to help them unlock the value of that data. So if they need to copy it up to the public Cloud and take advantage of it, we're going to integrate directly with Snowflake to make that really easy to do. >> So there are engineering integrations here, obviously that's required. Can you describe what that looks like? Give us the details on when it's available. >> Sure. So it's going to be sort of second half this year that you'll see, we're demoing it this week, but the availability we second half this year. And fundamentally, it's the way Clark described it, that Snowflake will reach into our S3 interface using the standard S3 interface. We're qualifying between the way they expect that S3 interface to present the data and the way our platform works, just to ensure that there's smooth interaction between the two. So that's sort of the first simplest use case. And then the second example we gave where the customer can copy some of that data up to the public Cloud. We're basically copying between two S3 buckets and making sure that Snowflake's Snowpipe is aware that data's being made available and can easily ingest it. >> And then that just goes into a virtual warehouse- >> Exactly. >> and customer does to know or care. >> Yep Exactly. >> Yeah. >> The compute happens in Snowflake the way it does in any other manner. >> And I know you got to crawl, walk, run second half of this year, but I would imagine, okay, you're going to start with AWS, correct? And then eventually you go to other Clouds. I mean, that's going to take other technical integrations, I mean, obviously. So should we assume there's a roadmap here or is this a one and done? >> I would assume that, I mean, based on our multi-Cloud approach, that's kind of our approach at least, yeah. >> Kind of makes sense, right? I mean, that would seem to be a natural progression. My other thought was, okay, I've got operational systems. They might be transaction systems running on a on a PowerMax. >> Yeah. >> Is there a way to get the data into an object store and make that available, now that opens up even more workloads. I know you're not committing to doing that, but it just, conceptually, it seems like something a customer might want to do. >> Yeah. I, a hundred percent, agree. I mean, I think when we brought our team together we started with a blank slate. It was what's the best solution we can build. We landed on this sort of first step, but we got lots of feedback from a lot of our big joint customers about you know, this system over there, this potential integration over here, and whether it's, you know, PowerMax type systems or other file workloads with native Snowflake data types. You know, I think this is just the beginning, right? We have lots of potential here. >> And I don't think you've announced pricing, right? It's premature for that. But have you thought about, and how are you thinking about the pricing model? I mean, you're a consumption based pricing, is that kind of how this is going to work? Or is it a sort of a new pricing model or haven't you figured that out yet? >> I don't know if you've got any details on that, but from a Snowflake perspective, I would assume it's consistent with how our customers engage with us today. >> Yeah. >> And we'll offer both possibilities, right? So you can either continue with the standard, you know, sort of CapEx motion, maybe that's the most optimal for you from a cost perspective, or you can take advantage through our OpEx option, right? So you can do consumption on-prem also. >> Okay. So it could be a dual model, right? Depending on what the customer wants. If they're a Snowflake customer, obviously it's going to be consumption based, however, you guys price. What's happening, Clark, in in the market? Explain why Snowflake has so much momentum and, you know, traction in the marketplace. >> So like I spent a lot of time doing analysis on why we win and lose, core part of my role. And, you know, there's a couple of, there's really three things that come up consistently as to why people people are really excited about Snowflake platform. One is the most simplest thing of all. It feels like is just ease of use and it just works, right? And I think the way that this platform was built for the Cloud from the ground up all the way back 10 years ago, really a lot allows us to deliver that seamless experience of just like instant compute when you want it, it goes away, you know, only pay for what you use. Very few knobs to turn and things like that. And so people absolutely love that factor. The other is multi-Cloud. So, you know, there's definitely a lot of organizations out there that have a multi-Cloud strategy, and, you know, what that means to them can be highly variable, but regardless, they want to be able to interact across Clouds in some capacity. And of course we are a single platform, like literally one single interface, consistent across all the three Cloud providers that we work upon. And it gives them that flexibility to mix and match Cloud infrastructure under any Snowflake however they see fit. The last piece of it is sharing. And, you know, I think it's that ability as I kind of alluded to around like breaking down organizational silos, and allow people to be able to actually connect with each other in ways that you couldn't do before. Like, if you think about how you and I would've shared data before, I'd be like, "Hey, Dave, I'm going to unload this table into a spreadsheet and I'm going to send it over in email." And there's the whole host of issues that get introduced in that and world, now it's like instantly available. I have a lot of control over it, it's governed it's all these other things. And I can create kind of walled gardens, so to speak, of how far out I want that to go. It could be in a controlled environment of organizations that I want to collaborate with, or I can put it on our marketplace and expose it to the whole world, because I think there's a value in that. And if I choose I can monetize it, right? So those, you know, the ease of use aspect of it, absolutely, it's just a fantastic platform. The multi-Cloud aspect of it and our unique differentiation around sharing in our marketplace and monetization. >> Yeah, on the sharing front. I mean, it's now discoverable. Like if you send me an email, like what'd you call that? When did you send that email? And then the same time I can forward that to somebody else's not governed. >> Yeah. >> All right. So that just be creates a nightmare for the compliance. >> Right. Yeah. You think about how you revoke access in that situation. You just don't, right? Now I can just turn it off and you go in to run your query. >> Don't get access on that data anymore. Yeah. Okay. And then the other thing I wanted to ask you, Clark is Snowflake started really as analytics platform, simplifying data warehousing, you're moving into that world of data science, you know, the whole data lake movement, bringing those two worlds together. You know, I was talking to Ben Ward about this, maybe there's a semantic layer that helps us kind of talk between those two worlds, but you don't care, right? If it's in an object store, it can play in both of those worlds, right? >> That's right. >> Yeah, it's up to you to figure it out and the customer- >> Yeah. >> from a storage standpoint. Here it is, serve it up. >> And that's the thrust of this announcement, right? Is bringing together two great companies, the Dell platform, the Snowflake platform, and allowing organizations to bring that together. And they decide like it, as we all know, customers decide how they're going to build their architecture. And so this is just another way that we're helping them leverage the capabilities of our two great platforms. >> Does this push or pull or little bit of both? I mean, where'd this come from? Or customers saying, "Hey, it would be kind of cool if we could have this." Or is it more, "Hey, what do you guys think?" You know, where are you at with that? >> It was definitely both, right? I mean, so we certainly started with, you know, a high level idea that, you know, the technologies are complimentary, right? I mean, as Clark just described, and at the same time we had customers coming to us saying, "Hey, wait a minute, I'm doing this over here, and this over here, how can I make this easier?" So that was like I said, we started with a blank sheet and lots of long customer conversations and this is what resulted. So >> So what are the sequence of events to kind of roll this out? You said it's second half, you know, when do you start getting customers involved? Do you have your already, you know, to poke at this and what's that look like? >> Yeah, sure. I can weigh in there. So, absolutely. We've had a few of our big customers that have been involved sort of in the design already who understand how they want to use it. So I think our expectation is that now that the sort of demonstrations have been in place, we have some pre functionality, we're going to see some initial testing and usage, some beta type situations with our customers. And then second half, we'll ramp from there. >> It's got to be a huge overlap between Dell customers and Snowflake customers. I mean, it's hundred billion. You can't not bump into Dell somewhere. >> Exactly. Yeah, you know. >> So where do you guys want to see this relationship go, kind of how should we measure success? Maybe you could each give your perspectives of that. >> I mean, for us, I think it's really showing the value of the Snowflake platform in this new world where there's a whole new ecosystem of data that is accessible to us, right? So seeing those organizations that are saying like, "Look, I'm doing new things with on-premises data that I didn't think that I could do before", or, "I'm driving efficiency in how I do analytics, and data engineering, and data science, in ways that I couldn't do before," 'cause they were locked out of using a Snowflake-like technology, right? So I think for me, that's going to be that real excitement. I'm really curious to see how the collaboration and the sharing component comes into this, you know, where you can think of having an on-premises data strategy and a need, right? But you can really connect to Cloud native customers and partners and suppliers that live in the Snowflake ecosystem, and that wasn't possible before. And so that is very conceivable and very possible through this relationship. So seeing how those edges get created in in our world and how people start to collaborate across data, both in the Cloud and on-prem is going to be really exciting. >> I remember I asked Frank, it was kind of early in the pandemic. I asked him, come on, tell me about how you're managing things. And he was awesome. And I asked him to at the time, you know, "You're ever going to do, you know, bring this platform on-prem?" He's like unequivocal, "No way, that's never going to happen. We're not going to do it halfway house ware Cloud only." And I kept thinking, but there's got to be a way to expand that team. There's so much data out there, and so boom, now we see the answer . Martin, from your standpoint, what does success look like? >> I think it starts with our partnership, right? So I've been doing this a long time. Probably the first time I've worked so closely with a partner like Snowflake. Joint customer conversations, joint solutioning, making sure what we're building is going to be really, truly as useful as possible to them. And I think we're going to let them guide us as we go forward here, right? You mentioned, you know, systems or record or other potential platforms. We're going to let them tell us where exactly the most value will come from the integration between the two companies. >> Yeah. Follow data. I mean, remember in the old days a hardware company like Dell would go to an ISP like Snowflake and say, "Hey, we ran some benchmarks. Your software runs really fast on our hardware, can we work together?" And you go, "Yeah, of course. Yeah, no problem." But wow! What a different dynamic it is today. >> Yeah. Yeah, absolutely. >> All right guys. Hey, thanks so much for coming to theCube. It's great to see you. We'll see you at the Snowflake Summit in June. >> Snowflake Summit in a month and a half. >> Looking forward to that. All right. Thank you again. >> Thank you Dave. >> All right. Keep it right there everybody. This is Dave Vellante, wall to wall coverage of Dell Tech World 2022. We'll be right back. (gentle music)

>> theCube presents Dell Technologies World, brought to you by Dell. >> Hi everyone, welcome back to Dell Technologies World 2022. You're watching theCube's coverage of this, three-day coverage wall to wall. My name is David Vellante John Furrier's here, Lisa Martin, David Nicholson. Talk of the town here is data. And one of the big announcements at the show is Snowflake and Dell partnering up, building ecosystems. Snowflake reaching into on-prem, allowing customers to actually access the Snowflake Data Cloud without moving the data or if they want to move the data they can. This is really one of the hotter announcements of the show. Martin Glynn is here, he's the Senior Director of Storage Product Management at Dell Technologies. And Clark Patterson, he's the Head of Product Marketing for Snowflake. Guys, welcome. >> Thanks for having us. >> So a lot of buzz around this and, you know, Clark, you and I have talked about the need to really extend your data vision. And this really is the first step ever you've taken on-prem. Explain the motivation for this from your customer's perspective. >> Yeah. I mean, if you step back and think about Snowflake's vision and our mission of mobilizing the world's data, it's all around trying to break down silos for however customers define what a silo is, right? So we've had a lot of success breaking down silos from a workload perspective where we've expanded the platform to be data warehousing, and data engineering, and machine learning, and data science, and all the kind of compute intensive ways that people work with us. We've also had a lot of success in our sharing capabilities and how we're breaking down silos of organizations, right? So I can share data more seamlessly within my team, I can do it across totally disparate organizations, and break down silos that way. So this partnership is really like the next leg of the stool, so to speak, where we're breaking down the silos of the the data and where the data lives ultimately, right? So up until this point, Cloud, all focus there, and now we have this opportunity with Dell to expand that and into on-premises world and people can bring all those data sets together. >> And the data target for this Martin, is Dell ECS, right? Your object store, and it's got S3 compatibility. Explain that. >> Yeah, we've actually got sort of two flavors. We'll start with ECS, which is our turnkey object storage solution. Object storage offers sort of the ultimate in flexibility, you know, potential performance, ease of use, right? Which is why it fits so well with Snowflake's mission for sort of unlocking, you know, the data within the data center. So we'll offer it to begin with ECS, and then we also recently announced our software defined object scale solution. So add even more flexibility there. >> Okay. And the clock, the way it works is I can now access non-native Snowflake data using what? Materialized views, external tables, how does that work? >> Some combination of all the above. So we've had in Snowflake a capability called external tables which we refer to, it goes hand in hand with this notion of external stages. Basically through the combination of those two capabilities, it's a metadata layer on data wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud up until this point. So it's effectively an extension of that functionality into the Dell on-premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake so that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> Okay. So for a while you've allowed non-native Snowflake data but it had to be in the Cloud. >> Correct. >> It was the first time it's on-prem, >> that's correct >> that's the innovation here. Okay. And if I want to bring it into the Cloud, can I? >> Yeah, the connection here will help in a migration sense as well, right? So that's the good thing is, it's really giving the user the choice. So we are integrating together as partners to make connection as seamless as possible. And then the end user will say like, look I've got data that needs to live on-premises, for whatever reasons, data sovereignty whatever they decide. And they can keep it there and still do the analytics in another place. But if there's a need and a desire to use this as an opportunity to migrate some of that data to Cloud, that connection between our two platforms will make that easier. >> Well, Michael always says, "Hey, it's customer choice, we're flexible." So you're cool with that? That's been the mission since we kind of came together, right? Is if our customers needed to stay in their data center, if that makes more sense from a cost perspective or, you know, a data gravity perspective, then they can do that. But we also want to help them unlock the value of that data. So if they need to copy it up to the public Cloud and take advantage of it, we're going to integrate directly with Snowflake to make that really easy to do. >> So there are engineering integrations here, obviously that's required. Can you describe what that looks like? Give us the details on when it's available. >> Sure. So it's going to be sort of second half this year that you'll see, we're demoing it this week, but the availability we second half this year. And fundamentally, it's the way Clark described it, that Snowflake will reach into our S3 interface using the standard S3 interface. We're qualifying between the way they expect that S3 interface to present the data and the way our platform works, just to ensure that there's smooth interaction between the two. So that's sort of the first simplest use case. And then the second example we gave where the customer can copy some of that data up to the public Cloud. We're basically copying between two S3 buckets and making sure that Snowflake's Snowpipe is aware that data's being made available and can easily ingest it. >> And then that just goes into a virtual warehouse- >> Exactly. >> and customer does to know or care. >> Yep Exactly. >> Yeah. >> The compute happens in Snowflake the way it does in any other manner. >> And I know you got to crawl, walk, run second half of this year, but I would imagine, okay, you're going to start with AWS, correct? And then eventually you go to other Clouds. I mean, that's going to take other technical integrations, I mean, obviously. So should we assume there's a roadmap here or is this a one and done? >> I would assume that, I mean, based on our multi-Cloud approach, that's kind of our approach at least, yeah. >> Kind of makes sense, right? I mean, that would seem to be a natural progression. My other thought was, okay, I've got operational systems. They might be transaction systems running on a on a PowerMax. >> Yeah. >> Is there a way to get the data into an object store and make that available, now that opens up even more workloads. I know you're not committing to doing that, but it just, conceptually, it seems like something a customer might want to do. >> Yeah. I, a hundred percent, agree. I mean, I think when we brought our team together we started with a blank slate. It was what's the best solution we can build. We landed on this sort of first step, but we got lots of feedback from a lot of our big joint customers about you know, this system over there, this potential integration over here, and whether it's, you know, PowerMax type systems or other file workloads with native Snowflake data types. You know, I think this is just the beginning, right? We have lots of potential here. >> And I don't think you've announced pricing, right? It's premature for that. But have you thought about, and how are you thinking about the pricing model? I mean, you're a consumption based pricing, is that kind of how this is going to work? Or is it a sort of a new pricing model or haven't you figured that out yet? >> I don't know if you've got any details on that, but from a Snowflake perspective, I would assume it's consistent with how our customers engage with us today. >> Yeah. >> And we'll offer both possibilities, right? So you can either continue with the standard, you know, sort of CapEx motion, maybe that's the most optimal for you from a cost perspective, or you can take advantage through our OpEx option, right? So you can do consumption on-prem also. >> Okay. So it could be a dual model, right? Depending on what the customer wants. If they're a Snowflake customer, obviously it's going to be consumption based, however, you guys price. What's happening, Clark, in in the market? Explain why Snowflake has so much momentum and, you know, traction in the marketplace. >> So like I spent a lot of time doing analysis on why we win and lose, core part of my role. And, you know, there's a couple of, there's really three things that come up consistently as to why people people are really excited about Snowflake platform. One is the most simplest thing of all. It feels like is just ease of use and it just works, right? And I think the way that this platform was built for the Cloud from the ground up all the way back 10 years ago, really a lot allows us to deliver that seamless experience of just like instant compute when you want it, it goes away, you know, only pay for what you use. Very few knobs to turn and things like that. And so people absolutely love that factor. The other is multi-Cloud. So, you know, there's definitely a lot of organizations out there that have a multi-Cloud strategy, and, you know, what that means to them can be highly variable, but regardless, they want to be able to interact across Clouds in some capacity. And of course we are a single platform, like literally one single interface, consistent across all the three Cloud providers that we work upon. And it gives them that flexibility to mix and match Cloud infrastructure under any Snowflake however they see fit. The last piece of it is sharing. And, you know, I think it's that ability as I kind of alluded to around like breaking down organizational silos, and allow people to be able to actually connect with each other in ways that you couldn't do before. Like, if you think about how you and I would've shared data before, I'd be like, "Hey, Dave, I'm going to unload this table into a spreadsheet and I'm going to send it over in email." And there's the whole host of issues that get introduced in that and world, now it's like instantly available. I have a lot of control over it, it's governed it's all these other things. And I can create kind of walled gardens, so to speak, of how far out I want that to go. It could be in a controlled environment of organizations that I want to collaborate with, or I can put it on our marketplace and expose it to the whole world, because I think there's a value in that. And if I choose I can monetize it, right? So those, you know, the ease of use aspect of it, absolutely, it's just a fantastic platform. The multi-Cloud aspect of it and our unique differentiation around sharing in our marketplace and monetization. >> Yeah, on the sharing front. I mean, it's now discoverable. Like if you send me an email, like what'd you call that? When did you send that email? And then the same time I can forward that to somebody else's not governed. >> Yeah. >> All right. So that just be creates a nightmare for the compliance. >> Right. Yeah. You think about how you revoke access in that situation. You just don't, right? Now I can just turn it off and you go in to run your query. >> Don't get access on that data anymore. Yeah. Okay. And then the other thing I wanted to ask you, Clark is Snowflake started really as analytics platform, simplifying data warehousing, you're moving into that world of data science, you know, the whole data lake movement, bringing those two worlds together. You know, I was talking to Ben Ward about this, maybe there's a semantic layer that helps us kind of talk between those two worlds, but you don't care, right? If it's in an object store, it can play in both of those worlds, right? >> That's right. >> Yeah, it's up to you to figure it out and the customer- >> Yeah. >> from a storage standpoint. Here it is, serve it up. >> And that's the thrust of this announcement, right? Is bringing together two great companies, the Dell platform, the Snowflake platform, and allowing organizations to bring that together. And they decide like it, as we all know, customers decide how they're going to build their architecture. And so this is just another way that we're helping them leverage the capabilities of our two great platforms. >> Does this push or pull or little bit of both? I mean, where'd this come from? Or customers saying, "Hey, it would be kind of cool if we could have this." Or is it more, "Hey, what do you guys think?" You know, where are you at with that? >> It was definitely both, right? I mean, so we certainly started with, you know, a high level idea that, you know, the technologies are complimentary, right? I mean, as Clark just described, and at the same time we had customers coming to us saying, "Hey, wait a minute, I'm doing this over here, and this over here, how can I make this easier?" So that was like I said, we started with a blank sheet and lots of long customer conversations and this is what resulted. So >> So what are the sequence of events to kind of roll this out? You said it's second half, you know, when do you start getting customers involved? Do you have your already, you know, to poke at this and what's that look like? >> Yeah, sure. I can weigh in there. So, absolutely. We've had a few of our big customers that have been involved sort of in the design already who understand how they want to use it. So I think our expectation is that now that the sort of demonstrations have been in place, we have some pre functionality, we're going to see some initial testing and usage, some beta type situations with our customers. And then second half, we'll ramp from there. >> It's got to be a huge overlap between Dell customers and Snowflake customers. I mean, it's hundred billion. You can't not bump into Dell somewhere. >> Exactly. Yeah, you know. >> So where do you guys want to see this relationship go, kind of how should we measure success? Maybe you could each give your perspectives of that. >> I mean, for us, I think it's really showing the value of the Snowflake platform in this new world where there's a whole new ecosystem of data that is accessible to us, right? So seeing those organizations that are saying like, "Look, I'm doing new things with on-premises data that I didn't think that I could do before", or, "I'm driving efficiency in how I do analytics, and data engineering, and data science, in ways that I couldn't do before," 'cause they were locked out of using a Snowflake-like technology, right? So I think for me, that's going to be that real excitement. I'm really curious to see how the collaboration and the sharing component comes into this, you know, where you can think of having an on-premises data strategy and a need, right? But you can really connect to Cloud native customers and partners and suppliers that live in the Snowflake ecosystem, and that wasn't possible before. And so that is very conceivable and very possible through this relationship. So seeing how those edges get created in in our world and how people start to collaborate across data, both in the Cloud and on-prem is going to be really exciting. >> I remember I asked Frank, it was kind of early in the pandemic. I asked him, come on, tell me about how you're managing things. And he was awesome. And I asked him to at the time, you know, "You're ever going to do, you know, bring this platform on-prem?" He's like unequivocal, "No way, that's never going to happen. We're not going to do it halfway house ware Cloud only." And I kept thinking, but there's got to be a way to expand that team. There's so much data out there, and so boom, now we see the answer . Martin, from your standpoint, what does success look like? >> I think it starts with our partnership, right? So I've been doing this a long time. Probably the first time I've worked so closely with a partner like Snowflake. Joint customer conversations, joint solutioning, making sure what we're building is going to be really, truly as useful as possible to them. And I think we're going to let them guide us as we go forward here, right? You mentioned, you know, systems or record or other potential platforms. We're going to let them tell us where exactly the most value will come from the integration between the two companies. >> Yeah. Follow data. I mean, remember in the old days a hardware company like Dell would go to an ISP like Snowflake and say, "Hey, we ran some benchmarks. Your software runs really fast on our hardware, can we work together?" And you go, "Yeah, of course. Yeah, no problem." But wow! What a different dynamic it is today. >> Yeah. Yeah, absolutely. >> All right guys. Hey, thanks so much for coming to theCube. It's great to see you. We'll see you at the Snowflake Summit in June. >> Snowflake Summit in a month and a half. >> Looking forward to that. All right. Thank you again. >> Thank you Dave. >> All right. Keep it right there everybody. This is Dave Vellante, wall to wall coverage of Dell Tech World 2022. We'll be right back. (gentle music)

>> Announcer: From around the globe it's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> And welcome back here on theCUBE. John Walls, your host with you as we continue our IBM Think 2021 initiative. Been talking a lot about IBM's assistance in terms of what it's doing for its client-base. We're going to talk about partnerships today, a little bit with Bill Patterson who is the EVP and General Manager of CRM Applications at Salesforce who has a really good partnership in great practice right now, with IBM. And Bill, thanks for the time today. Lookin' forward to spending some time with you, here. >> Yeah, thank you John, thanks for having me today. >> You bet. Well, let's just jump right in. First off, let's share with the viewers about your core responsibilities at Salesforce. We talked about CRM, what your engagement is there, but if you would just kind of of give us an idea of the kind of things that you're handling on a day-to-day basis. >> Well, I am responsible for our CRM applications here, at Salesforce, which are our sales cloud technologies to help organizations get back to growth, our service cloud technologies which are really helping organizations to take care of their customers, you know, through all moments of the digital lifecycle, our small business solutions, so to help growing organizations thrive, and our Work.com and vaccine management solutions which are helping the economy safely reopen through the crisis modes that we've all been living in. So broad range responsibilities and my day-to-day is nothing like it was a year ago. >> Yeah and I could only imagine, especially when you throw that last component in, COVID, which hopefully, we'll have time to talk about just because, I think, people are so are taken to the subject now and obviously it's impacting business on so many different levels. But let's talk, first off, about IBM and your partnership with them, kind of the genesis of that, how that came about, and maybe how you're working together. How are you integrated these days with IBM? >> Well, you know, one of the things at Salesforce that are key value as an organization is is to establish trust around the transformation of organizations across the world. And when you think about brands that you can trust to drive transformations with, IBM and Salesforce really stand apart. So IBM is an incredible partner for us on the technology side, on a service delivery side, and in an innovation side for us to create new solutions to help our clients really go in this from-to state of how their businesses used to operate to how they need to operate in the future. I loved working with the IBM team. We have a lot of great values that are shared across our two organizations. But most fundamentally, those values are deeply rooted in customer success. And I think that that is one of the things that really draws me too, working with such a great partner here. >> Go into the process a little bit, if you will. So if I'm a prospective client of yours and I come to you with some cloud needs, you know, again, whether it's storage or whether it's applications or whether it's Edge, whatever it is I'm coming to you for, how do you then translate that to IBM and how does IBM come into play, where do the boundaries kind of start and stop or do they? Or is it a complete mesh? >> Yeah, well I think one of the things that's sort of unique about today's climate is people aren't just looking to solve technology problems, they're looking to solve business problems. And what we really do at Salesforce is lead with the business transformation opportunity and deeply partner with IBM on a number of fronts to really go help those opportunities become realized. The first is in the services line. IBM has great partnerships with Salesforce around the transformation about core business processes, configuration, integration services. That's one of the dimensions that we work together on. We also work together on areas of artificial intelligence and how we help businesses become smart in their operations every day to empower their workforce to really achieve more. And finally, you know that you mentioned about core technology, you know, oftentimes, the business requirements translate into great technology transformation. And that's what we do deeply with the IBM team is really outlining a blueprint and a roadmap for modernizing the technical infrastructure to help organizations move fast, increase their operational agility, and run at such scale and safely in today in the modern world that we all operate in on. So through all those facets of the lifecycle, IBM continues to be one of our leading partners, globally, to help clients, you know, not just here, in the United States, but around the world to think about how they need to maximize their transformational abilities. >> Yeah, and you touched on this at the outset of the interview. We were talking about IBM and the impact and obviously, the great association relationship that you have with them and the value in that. I'd like you to amplify on that a little bit more in terms of, specifically, what are you getting out of it you think, from a Salesforce perspective to have kind of the power and the weight and the bench, basically, that IBM provides. >> Well you think about transformation and you know, you read a lot about digital transformation online, that means so many different things to so many different businesses. Businesses, not just, like I said, here in one country, but globally, the transformational needs really need to come with incredible bench and domain expertise by industry, by geography, even by some micro-regions in those geographies given what we've been experiencing here, in the public sector in the United States with this COVID response activity we've been doing with the IBM team. And so when you talk about the deep bench, what I love about working with IBM on is, again, commanding just great industry insights and knowledge of where industries are heading and also cross-industry insights so that you can really bring great best practices from say, one industry to another. Second is that real understanding of the global nature of business today. And I don't think the one thing that's fascinating about digital, it is not a sovereign identity, today. Digital really means that you need to understand how to operate in every country, every region, every location, you know, safely. And so IBM has incredible depth in bench of experiences to help our clients truly transform those areas. Maybe another area that I really have appreciated working with IBM on is that deep technical understanding and deep technical domain of excellence maybe in the area of artificial intelligence. And our partnership is quite unique between Salesforce and IBM. Not only do we work together for external clients but inside of IBM, IBM is using Salesforce today to run a lot of your core operations. And so the partnership we work with, not only IBM as a kind of delivery excellence, but internally as a customer, is really helping IBM transform its operations from service to sales to marketing all around the world. So I think this partnership is one that is deeply rooted in working together and really, like I mentioned before, finding the right path to drive the outcomes of tomorrow. >> You know, you mentioned COVID and so we'd like to touch on that. But I assume that's a big part of your current relationship, if you will, in terms of the partnership goes. What, specifically, are you doing with IBM in that space and what have you done, and then what are you continuing to do as we go through now, the vaccination process and the variant identification processes and all these things? So maybe you can share with our viewers a little bit about the kinds of things that you have been working on together and the kind of progress that you've been making. >> Well, back a year ago, you know, when the world was really at a standstill, Salesforce created a solution called Work.com which was to engineer new technologies to help businesses kind of deal with the reality of a hard shutdown to business in the, say, private sector and then in the public sector, to really create new innovation around key solutions like contact tracing that you might have needed to track, you know, kind of outbreak and the rate of progression of the virus. And what we did with the IBM team, working with clients around the world first was work together to deploy those technologies rapidly into the hands of our customers. Through those moments of opportunity and realization, you know, working with our clients, we also started to hear of, you know, kind of about where we find ourselves today, this mass vaccination wave of where our citizens and societies are kind of on the recovery journey. And the work that we did with IBM was to start to plan out the next wave of recovery options around vaccine managements, Salesforce creating a core vaccine scheduling, distribution, and administration management services and IBM focusing on more of that credentialing and vaccination state of how someone has gone from receiving a shot in arm to now having a trusted profile of which vaccines, when did you receive them, are they still accurate and valid around those solutions. So where we're working with the IBM team most acutely on COVID now is in the vaccine credential management side through Watson Health. >> Well, can you give us an idea now, let's see if we can dig in a little deeper on some of those other things you talked about to about core technologies, you talked about, I mentioned Edge, you know, and that's people tryin' to figure out how they integrate these Edge technologies into their primary systems, now. So can you give us some examples, some specific examples of some things that you're actually collaborating on today in those areas or maybe another that comes to mind? >> Yeah, Edge computing is probably one of the other more exciting things that we're doing with the IBM team and I think you find that really working with our field service business and IBM cloud services, you know, globally speaking. On the Edge, as devices become smarter and more digital, they have a lot of signals that organizations can now tap into, not only for real-time intelligence but also fault intelligence when a device is starting to need repair or preventative maintenance around the solutions that kind of need to be administered. And the work that we're doing to really broker this connected, not just enterprise, but connected sort of experiences with IBM, super powerful here, because the IBM Edge services are now helping us get into anomaly detection. Those anomaly detections are automatically routing to workers who use the Salesforce field service capabilities, and now we can help organizations stay running safely and with continuity which is really all our customers are asking us for. So the ability for us to be creative and understand, you know, our parts of the picture together are really the things that I think are most exciting for what we're doing for clients around the world. >> Yeah, you mentioned continuity, kind of a cousin to that, I think, is security in a way because you're-- >> Absolutely. >> So what are you hearing from your customer-base these days with regard to security? You know, a lot of high profile instances certainly from bad state actors, as we well know. But what are you hearing in terms of security that you're looking at and maybe cooperating or collaborating with IBM on to make sure that those concerns are being addressed? >> Yeah, you know, I think, well, first off, security is on the top of minds for all decision-makers, executives, today. It's the number one threat that a lot of companies are really needed to respond to given what we've seen in the geo-political world that we're in. And security isn't just about securing your servers, it's also about securing every operational touchpoint that you might have with, you know, your every end-user or even every customer that's inter-operating with your services that you project as an organization. And what I love about working with the IBM team is, as we mentioned, you know, such great insights across all parts of technology infrastructure to really help understand both the threat level, how to contain that threat level, and more importantly, how to engineer with, you know, great solutions all the way into the hands of customers so they become safe and easy for all actors in your environment to really operate with. And that's where, again, you know, you think about a solution like mobile sales professionals, they're out traveling around the world on mobile devices, sometimes, their AG even brought their own personal devices into the enterprise. And so IBM is a great partner for ours just to help us understand the overall threat level of every device every moment that an employee might have within their organizational data, and really help create great solutions to help keep organizations running safely. >> Yeah, I think it's interesting you tell about people bringing their own devices on, back when, I remember that acronym, BYOB was like a huge thing, right? (chuckling) And this major problem or conundrum and now it's almost like an afterthought, you've got it solved, you've got it well taken care of. >> Well you think about, again, devices in the enterprise and how much we've been able to achieve with the BYOB becoming commonplace and norm, even today, the workman place from home kind of environment that we're in. I mean, who would have thought a year ago that most of our operations can be conducted safely from our home offices, not just our regional or corporate offices? And again, that's the kind of thing that working with IBM has been such a great value for our clients because no one could have forecasted that the contact center would've had to moved to your kitchen last year. And yet, we had to really go achieve that in this time and working with great partners like IBM, it became not just a conversation but real practice. >> By the way, I think I said BYOB. I meant BYOD, so you know where my mind's at, right? (chuckling) >> I wasn't going to correct you. >> Hey thanks, Bill, I appreciate that. It just kind of hit me. I think that that just, that was a Freudian slip, certainly. Hey Bill, thanks for the time. I certainly do appreciate and thanks for shining a light on this really good partnership between Salesforce and IBM. And we wish you continued success down the road with that, as well. >> Yeah, thanks again. And again, love being your partner and love the impact we're having together. >> Great, thank you very much. Bill Patterson joining us, the EVP work in CRM at Salesforce talking about IBM and that relationship that they're putting into practice for their client-base. John Walls reporting here, on theCUBE. Thanks for joining us with more on IBM Think. (soft music) ♪ Dah de dah ♪ ♪ Dah ♪

>>from around the globe, >>it's the cube >>With digital coverage of IBM think 2021 brought to you by >>IBM. Welcome back here on the cube, jOHn wall is your host with you as we continue our IBM think initiative. Been talking a lot about IBM s assistance in terms of what it's doing for its client base. We're gonna talk about partnerships today a little bit with Bill Patterson who is the VP and general manager of Crm applications at Salesforce, who has a really good partnership in great practice right now with IBM and Bill, thanks for the time to you looking forward to spending some time with you hear, >>thank you Jon. Thanks for having me today. >>You bet. Let's just jump right in first off, let's share with the viewers about your core responsibilities that sales for us. We're talking about Crm what your engagement is there, but if you would just kind of give us an idea of the kind of things that you're handling on a day to day basis, >>Well I am responsible for our crm applications here at Salesforce, which are our sales cloud technologies to help organizations get back to growth. Our service cloud technologies which are really helping organizations to take care of their customers through all moments of the digital lifecycle are small business solutions. So to help growing organizations thrive uh and our work dot common vaccine management solutions which are helping economies safely reopen through the crisis modes that we've all been living in. So broad range of responsibilities in my day to day is nothing like it was a year ago. >>I could only imagine, especially when you throw that last component in Covid, which hopefully will have some time to talk about just because they people are so are taken to the subject now and obviously it's impacting business on so many different levels. But let's talk first off about IBM and your partnership with them kind of the genesis of that, how that came about and maybe how you're working together, how are you integrated these days with IBM? >>Well you know one of the things that Salesforce that are key value as an organization is is to establish trust around the transformation of organizations across the world and when you think about brands that you can trust to drive transformation with IBM and Salesforce really stand apart. Uh so IBM is an incredible partner for us, on the technology side, on a service delivery side and an innovation side for us to create new solutions to help our clients really go in this from two state of how their businesses used to operate to how they need to operate in the future. Um I love working with the IBM team, we have a lot of great values that are shared across our two organizations, but most fundamentally those values are deeply rooted in customer success. And I think that that is one of the things that really draws me to working with such a great partner here. >>Yeah. Go into the process a little bit if you will. So if I'm a prospective client of yours and I come to you with some cloud needs, you know, again, whether it's uh, you know, storage or whether it's applications or whether it's edge, whatever it is, you know, I'm coming to you for um how do you then translate that to IBM and how does IBM come into play? Where does where do the boundaries kind of start and stop or do they? Is it a complete mesh? >>Yeah. Well, I think one of the things that's sort of unique about today's climate is people aren't just looking to solve technology problems. They're looking to solve business problems and what we really do, you know, at Salesforce's lead with the business transformation opportunity uh, and deeply partnered with IBM on a number of fronts to really go help those opportunities become realized. The first is in the services line. IBM has great partnerships with Salesforce around the transformation about core business processes, configuration integration services. That's one of the dimensions that we work together on. We also worked together on the areas of artificial intelligence and how we help businesses become smart in their operations every day to empower their workforce to really achieve more. And finally, you know that you mentioned about core technology oftentimes the business requirements translate into great technology transformation and that's what we do deeply with the IBM team is really outlined a blueprint and a road map for modernizing the technical infrastructure to help organizations move fast, increase their operational agility and run at such scale and safely today in the modern world that we all operate in on so through all those facets of the life cycle, IBM continues to be one of our leading partners globally to help clients, you know, not just here in the United States but around the world think about how they need to maximize their transformational abilities. >>And you touched on this at the outset of the interview, we were talking about IBM and the impact and and obviously the great association relationship that you have with them and the value in that I'd like you to amplify on that a little bit more in terms of specifically what are you getting out of it you think from a sales force perspective to have kind of the power and the weight and the bench basically that IBM provides. >>Yeah, well you think about transformation and you know, you read a lot about digital transformation online, that means so many different things to so many different businesses, businesses not just like I said here in one country, but globally the transformational needs, you really need to come with incredible bench and domain expertise by industry, by geography. Even by, you know, some micro regions in those geography has given what we've been experiencing here in the public sector in the United States with the scope of response activity we're doing with the IBM team. And so when you talk about the deep bench, what I love about working with IBM on is again commanding just great industry insights and knowledge of where industries are heading uh and also cross industry insights so that you can really bring great best practices from say one industry to another Um second is that real understanding of the global nature of business today. And I don't think the one thing that's really fasting about digital, it is not a sovereign identity today, a digital really means that you need to understand how to operate in every country, every region, every location uh you know, safely and so IBM has incredible depth and bench of experiences to help our clients truly transform those areas. Maybe another area that I really have appreciated working with IBM on is that deep technical understanding and deep technical domain of excellence, you know, maybe in the area of artificial intelligence and our partnership is quite unique between Salesforce and IBM, not only do we work together for external clients, but inside of IBM, IBM is using Salesforce today to run a lot of your core operations. And so the partnership we work with not only IBM as a kind of delivery excellence, but internally as a customer is really helping IBM transform its operations from service to sales to marketing all around the world. So I think this partnership is one that is deeply rooted in in working together and really like I mentioned before, finding the right path to drive the outcomes >>of tomorrow, you know, you mentioned Covid, um and so I would like to touch on that, but I assume that's you know, a big part of of your current relationship, if you will in service of the partnership goes, what specifically are you doing with IBM in that space of what have you done? And then what are you continuing to do as we go through now, the vaccination process and the variant identification processes and all these things. So maybe you can share with our viewers a little bit about the kinds of things that you have been working on together and the kind of progress that you've been making. >>Yeah, well back, you know, a year ago, uh you know when the world was really at a standstill, uh sales first created a solution called work dot com, which was to engineer new technologies to help businesses kind of deal with the reality of a hard shutdown to business in the say prime um private sector and in the public sector to really create new innovation around key solutions like contact tracing that you might have needed to track, you know, kind of outbreak and uh you know, the rate of progression of the virus. And what we did with the IBM team, working with uh clients around the world, first was work together to deploy those technologies rapidly into the hands of our customers through those moments of opportunity and realization. You know, working with our clients, we also started here, you know, kind of about, you know, where we find ourselves today. This mass vaccination wave of where our citizens and societies are kind of on the recovery journey. And the work that we did with IBM was to start to plan out the next wave of recovery options around vaccine management sales force, creating the core vaccine scheduling, distribution in administration management services in IBM focusing on more of that credentialing and vaccination state of how someone has gone from receiving a shot and arm to now having a trusted profile of which vaccines. When did you receive them? Are they still accurate, valid? Uh, around those solutions. So where we're working with the IBM tape most acutely on covid now is in the vaccine credential management side through Watson health. >>Mm Well, can you give us an idea now? Let's if we can dig in a little deeper on some other things you talk about? Talk about core technologies, we talked about, I mentioned Edge you know, that's when people are trying to figure out how to integrate, you know, these edge technologies into their, into their primary systems now. So, um can you give us some examples, some specific examples of some things that you're actually collaborating on today in those areas or maybe another that comes to mind? >>Yeah. Edge computing is probably one of the other more exciting things that we're doing with the IBM team. And I think you find that really working with our field service business and IBM cloud services, you know, globally speaking on the edge, you know, as devices become smarter and more digital. Um, they have a lot of signals that organizations can now tap into not only for real time intelligence, but also fault intelligence. When a device actually is starting to need repair or preventative maintenance around the solutions that kind of need to be administered and the work that we're doing to really broker this connected, not just enterprise, but connected set of experiences, but by IBM super powerful here because the IBM edge services are now helping us get into anomaly detection, those anomaly detection czar automatically routing to workers who use the sales force field service capabilities. And now we can help organizations stay running uh, you know, safely and and with continuity, which is really all our customers are asking us for. So the ability for us to be creative and understand our parts of the picture together are really the things that I think are most exciting um for what we're doing for clients around >>the world. Now, you mentioned continuity, kind of a cousin of that and a security right, in a way, because, you know, um so what are you hearing from your your customer base these days with regard to security? You know, a lot of very high profile instances, certainly from bad state actors, as we will know. But what are you hearing in terms of security that you're looking at and maybe cooperating and collaborating with IBM on to make sure that those concerns are being addressed? >>Yeah. You know, I think, well, first off security is on the top of mines, you know, for all decision makers, executives today, it's the number one threat that a lot of companies are really needing to respond to, given what we've seen, uh you know, in the geopolitical world that we're in. Um and security isn't just about securing your servers, it's also about securing every operational touch point that you might have with, you know, your um uh every end user or even every customer that's inter operating with your services that you project as an organization. And what I love about working with the IBM team as we mentioned, you know, just such great insights across all parts of technology infrastructure to really help understand both the threat level, uh how to contain that threat level, and more importantly how to engineer, you know, with great solutions all the way into the hands of customers so that becomes safe and easy for all actors in your environment to really operate with. Um And that's where, you know, again, you think about a solution like mobile sales professionals, you know, they're out traveling around the world on mobile devices, sometimes they're even brought their own personal devices into the enterprise. And so IBM is a great partner for ours just to help us understand the overall threat level of every device, every moment that an employee might have within their organizational data and really helped create great solutions to keep organizations running >>safely. Yeah, I think it's uh interesting you talk about people bringing their own devices on back when I remember that from B y O B was like a huge thing, right? And this major problem or a conundrum and now it's, it's almost like an afterthought right? You got it solved, we got it well, taken care of, >>oh, you think about again, devices in the enterprise and how much we've been able to achieve with the will be becoming commonplace in norm even today, the working place from home kind of environment that we're in, I mean, who would have thought a year ago that most of our operations conducted safely from her home office is not just our regional and corporate offices. And again, that's the kind of thing that working with IBM has been such a great value for our clients because you know, no one could have forecasted that the context center would have had to move to your kitchen last year. Uh and yet, you know, we had to really go achieve that in this time and working great partners like IBM, it became not just a conversation but real practice. >>Right by the way, I think I said, B Y O. B. I met B Y O. D. And so you know where my mind's at? Uh >>I wasn't gonna correct you. I appreciate that. It's >>Just kind of hit me. I think that just that was a 40 and slip. Certainly. >>Hey Bill, thanks for >>the time. I certainly do appreciate it. Thanks for shining light on this really good partnership between Salesforce and IBM. And we wish you continued success down the road with that as well. >>Yeah. Thanks again and again. Love being your partner and love the impact we're having together. >>Great! Thank you very much. Bill Patterson joining us, the VP working Crm at Salesforce, talking about IBM and that relationship that they're putting into practice for their client base. John Wall's reporting here on the cube. Thanks for joining us with more on IBM thing. Yeah.

>> Announcer: Live from San Francisco, it's theCUBE. covering Spark Summit 2017, brought to you by Databricks. (techno music) >> Welcome to theCUBE, at Spark Summit here at San Francisco, at the Moscone Center West, and we're going to be competing with all the excitement happening behind us. They're going to be going off with raffles, and I don't know what all. But we'll just have to talk above them, right? >> Clarke: Well at least we didn't get to win. >> Our next guest here on the show is Clarke Patterson from Confluent. You're the Senior Director of Product Marketing, is that correct? >> Yeah, you got it. >> All right, well it's exciting -- >> Clarke: Pleasure to be here >> To have you on the show. >> Clarke: It's my first time here. >> David: First time on theCUBE? >> I feel like one of those radio people, first time caller, here I am. Yup, first time on theCUBE. >> Well, long time listener too, I hope. >> Clarke: Yes, I am. >> And so, have you announced anything new that you want to talk about from Confluent? >> Yeah, I mean not particularly at this show per se, but most recently, we've done a lot of stuff to enable customers to adopt Confluent in the Cloud. So we came up with a Confluent Cloud offering, which is a managed service of our Confluent platform a couple weeks ago, at our event around Kafka. So we're really excited about that. It really fits that need where Cloud First or operation-starved organizations are really wanting to do things with storing platforms based on Kafka, but they just don't have the means to make it happen. And so, we're now standing this up as a managed service center that allows them to get their hands on this great set of capabilities with us as the back stop to do things with it. >> And you said, Kafka is not just a publish and subscribe engine, right? >> Yeah, I'm glad that you asked that. So, that one of the big misconceptions, I think, of Kafka. You know, it's made its way into a lot of organizations from the early use case of publish and subscribe for data. But, over the last 12 to 18 months, in particular, there's been a lot of interesting advancements. Two things in particular: One is the ability to connect, which is called a Connect API in Kafka. And it essentially simplifies how you integrate large amounts of producers and consumers of data as information flows through. So, a modernization of ETL, if you will. The second thing is stream processing. So there's a Kafka streams API that's built-in now as well that allows you to do the lightweight transformations of data as it flows from point A to point B, and you could publish out new topics if you need to manipulate things. And it expands the overall capabilities of what Kafka can do. >> Okay, and I'm going to ask George here to dive in, if you could. >> And I was just going to ask you. >> David: I can feel it. (laughing) >> So, this is interesting. But if we want to frame this in terms of what people understand from, I don't want to say prehistoric eras, but earlier approaches to similar problems. So, let's say, in days gone by, you had an ETL solution. >> Clarke: Yup. >> So now, let's put Connect together with stream processing, and how does that change the whole architecture of integrating your systems? >> Yeah, I mean I think the easiest way to think about this is if you think about some of the different market segments that have existed over the last 10 to 20 years. So data integration was all about how do I get a lot of different systems to integrate a bunch of data and transform it in some manner, and ship it off to some other place in my business. And it was really good at building these end-to-end workflows, moving big quantities of data. But it was generally kind of batch-oriented. And so we've been fixated on, how do we make this process faster? To some degree, and the other segment is application integration which said, hey, you know when I want applications to talk to one another, it doesn't have the scale of information exchange, but it needs to happen a whole lot faster. So these real-time integration systems, ESBs, and things like that came along and it was able to serve that particular need. But as we move forward into this world that we're in now, where there's just all sorts of information, companies want to become advanced-centric. You need to be able to get the best of both of those worlds. And this is really where Kafka is starting to sit. It's saying, hey let's take massive amounts of data producers that need to connect to massive amounts of data consumers, be able to ship a super-granular level of information, transform it as you need, and do that in real-time so that everything can get served out very, very fast. >> But now that you, I mean that's a wonderful and kind of pithy kind of way to distill it. But now that we have this new way of thinking of app integration, data integration, best of both worlds, that has sort of second order consequences in terms of how we build applications and connect them. So what does that look like? What do applications look like in the old world and now what enables them to be sort of re-factored? Or for new apps, how do you build them differently? >> Yeah, I mean we see a lot of people that are going into microservices oriented architecture. So moving away from one big monolithic app that takes this inordinate amount of effort to change in some capacity. And quite frankly, it happens very, very slow. And so they look to microservices to be able to split those up into very small, functional components that they can integrate a whole lot faster, decouple engineering teams so we're not dependent on one another, and just make things happen a whole lot quicker than we could before. But obviously when you do that, you need something that can connect all those pieces, and Kafka's a great thing to sit in there as a way to exchange state across all these things. So that's a massive use case for us and for Kafka specifically in terms of what we're seeing people do. >> You've said something in there at the end that I want to key off, which is, "To exchange state." So in the old world, we used a massive shared database to share state for a monolithic app or sometimes between monolithic apps. So what sort of state-of-the-art way that that's done now with microservices, if there's more than one, how does that work? >> Yeah, I mean so this is kind of rooted in the way we do stream processing. So there's this concept of topics, which effectively could align to individual microservices. And you're able to make sure that the most recent state of any particular one is stored in the central repository of Kafka. But then given that we take an API approach to stream processing, it's easy to embed those types of capabilities in any of the end-points. And so some of the activity can happen on that particular front, then it all gets synchronized down into the centralized hub. >> Okay, let me unpack that a little bit. Because you take an API approach, that means that if you're manipulating a topic, you're processing a microservice and that has state in it? Is that the right way to think about it? >> I think that's the easiest way to think about it, yeah. >> Okay. So where are we? Is this a 10 year migration, or is it a, some certain class of apps will lend themselves well to microservices, legacy apps will stay monolithic, and some new apps, some new Greenfield apps, will still be database-centric? How do you, or how should customers think about that mix? >> Yeah that's a great question. I don't know that I have the answer to it. The best gauge I can have is just the amount of interest and conversations that we have on this particular topic. I will say that from one of the topics that we do engage with, it's easily one of the most popular that people are interested in. So if that's a data point, it's definitely a lot of interested people trying to figure out how to do this stuff very, very fast. >> How to do the microservices? >> Yeah and I think if you look at some of the more notable tech companies of late, they're architected this way from the start. And so everyone's kind of looking at the Netflix of the world, and the Ubers of the world saying, I want to be like those guys, how do I do that? And it's driving them down this path. So competitive pressure, I think, will help force people's hands. The more that your competitors are getting in front of you and are able to deliver a better customer experience through some sort of mobile app or something like that, then it's going to force people to have to make these changes quicker. But how long that takes it'll be interesting to see. >> Great! Great stuff. Switch gears just a little bit. Talk about maybe why you're using Databricks and what some of the key value you've gotten out of that. >> Yeah, so I wouldn't say that we're using Databricks per se, but we integrate directly with Spark. So if you look at a lot of the use cases that people use Spark for, they need to obviously get data to where it is. And some of the principles that I said before about Kafka generally, it's a very flexible, very dynamic mechanism for taking lots of sources of information, culling all that down into one centralized place and then distributing it to places such as Spark. So we see a lot of people using the technologies together to get the data from point A to point B, do some transformation as they so need, and then obviously do some amazing computing horsepower and whatnot in Spark itself. >> David: All right. >> I'm processing this, and it's tough because you can go in so many different directions, especially like the question about Spark. I guess, give us some of the scenarios where Spark would fit. Would it be like doing microservices that require more advanced analytics, and then they feed other topics, or feed consumers? And then where might you stick with a shared database that a couple services might communicate with, rather than maintaining the state within the microservice? >> I think, let me see if I can kind of unpack that myself a little bit. >> George: I know it was packed pretty hard. (laughing) >> Got a lot packed in there. When folks want to do things like, I guess when you think about it like an overall business process. If you think about something like an order to cash business process these days, it has a whole bunch of different systems that hang off it. It's got your order processing. You've got an inventory management. Maybe you've got some real-time pricing. You've got some shipments. Things, like that all just kind of hang off of the flow of data across there. Now with any given system that you use for addressing any answers to each of those problems could be vastly different. It could be Spark. It could be a relational database. It could be a whole bunch of different things. Where the centralization of data comes in for us is to be able to just kind of make sure that all those components can be communicating with each other based on the last thing that happened within each of them individually. And so their ability to embed transformation, data transformations and data processing in themselves and then publish back out any change that they had into the shared cluster subsequently makes that state available to everybody else. So that if necessary, they can react to it. So in a lot of ways, we're kind of agnostic to the type of processing that happens on the end-points. It's more just the free movement of all the data to all those things. And then if they have any relevant updates that need to make it back to any of the other components hanging on that process flow, they should have the ability to publish that back down it. >> And so one thing that Jay Kreps, Founder and CEO, talks about is that Kafka may ultimately, or in his language, will ultimately grow into something that rivals the relational database. Tell us what that world would look like. >> It would be controversial (laughing). >> George: That's okay. >> You want me to be the bad guy? So it's interesting because we did Kafka Summit about a month ago, and there's a lot of people, a lot of companies I should say, that are actually using and calling Kafka an enterprise data hub, a central hub for data, a data distribution network. And they are literally storing all sorts (raffle announcements beginning on loudspeaker) of different links of data. So one interesting example was the New York Times. So they used Kafka and literally stored every piece of content that has ever been generated at that publisher since the beginning of time in Kafka. So all the way back to 1851, they've obviously digitized everything. And it sits in there, and then they disposition that back out to various forms of the business. So that's -- >> They replay it, they pull it. They replay and pull, wow, okay. >> So that has some very interesting implications. So you can replay data. If you run some analytics on something and you didn't get the result that you wanted, and you wanted to redo it, it makes it really easy and really fast to be able to do that. If you want to bring on a new system that has some new functionality, you can do that really quickly because you have the full pedigree of everything that sits in there. And then imagine this world where you could actually start to ask questions on it directly. That's where it starts to get very, very profound, and it will be interesting to see where that goes. >> Two things then: First, it sounds, like a database takes updates, so you don't have a perfect historical record. You have a snapshot of current values. Like whereas in a log, like Kafka, or log-structured data structure you have every event that ever happened. >> Clarke: Correct. >> Now, what's the impact on performance if you want to pull, you know -- >> Clarke: That much data? >> Yeah. >> Yeah, I mean so it all comes down to managing the environment on which you run it. So obviously the more data you're going to store in here, and the more type of things you're going to try to connect to it, you're going to have to take that into account. >> And you mentioned just a moment ago about directly asking about the data contained in the hub, in the data hub. >> Clarke: Correct. >> How would that work? >> Not quite sure today, to be honest with you. And I think this is where that question, I think, is a pretty provocative one. Like what does it mean to have this entire view of all granular event streams, not in some aggregated form over time? I think the key will be some mechanism to come onto an environment like this to make it more consumable for more business types users. And that's probably one of the areas we'll want to watch to see how that's (background noise drowns out speaker). >> Okay, only one unanswered question. But you answered all the other ones really well. So we're going to wrap it up here. We're up against a loud break right now. I want to think Clarke Patterson from Confluent for joining us. Thank you so much for being on the show. >> Clarke: Thank you for having me. >> Appreciate it so much. And thank you for watching theCUBE. We'll be back after the raffle in just a few minutes. We have one more guest. Stay with us, thank you. (techno music)

>> From theCUBE Studios in Palo Alto, in Boston bringing you Data Driven Insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> In the pre-cloud era hardware companies would run benchmarks, showing how database and or application performance ran better on their systems relative to competitors or previous generation boxes. And they would make a big deal out of it. And the independent software vendors, you know they'd do a little golf clap if you will, in the form of a joint press release it became a game of leaprog amongst hardware competitors. That was pretty commonplace over the years. The Dell Snowflake Deal underscores that the value proposition between hardware companies and ISVs is changing and has much more to do with distribution channels, volumes and the amount of data that lives On-Prem in various storage platforms. For cloud native ISVs like Snowflake they're realizing that despite their Cloud only dogma they have to grit their teeth and deal with On-premises data or risk getting shut out of evolving architectures. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we unpack what little is known about the Snowflake announcement from Dell Technologies World and discuss the implications of a changing Cloud landscape. We'll also share some new data for Cloud and Database platforms from ETR that shows Snowflake has actually entered the Earth's orbit when it comes to spending momentum on its platform. Now, before we get into the news I want you to listen to Frank's Slootman's answer to my question as to whether or not Snowflake would ever architect the platform to run On-Prem because it's doable technically, here's what he said, play the clip >> Forget it, this will only work in the Public Cloud. Because it's, this is how the utility model works, right. I think everybody is coming through this realization, right? I mean, excuses are running out at this point. You know, we think that it'll, people will come to the Public Cloud a lot sooner than we will ever come to the Private Cloud. It's not that we can't run a private Cloud. It's just diminishes the potential and the value that we bring. >> So you may be asking yourselves how do you square that circle? Because basically the Dell Snowflake announcement is about bringing Snowflake to the private cloud, right? Or is it let's get into the news and we'll find out. Here's what we know at Dell Technologies World. One of the more buzzy announcements was the, by the way this was a very well attended vet event. I should say about I would say 8,000 people by my estimates. But anyway, one of the more buzzy announcements was Snowflake can now run analytics on Non-native Snowflake data that lives On-prem in a Dell object store Dell's ECS to start with. And eventually it's software defined object store. Here's Snowflake's clark, Snowflake's Clark Patterson describing how it works this past week on theCUBE. Play the clip. The way it works is I can now access Non-native Snowflake data using what materialized views, external tables How does that work? >> Some combination of the, all the above. So we've had in Snowflake, a capability called External Tables, which you refer to, it goes hand in hand with this notion of external stages. Basically there's a through the combination of those two capabilities, it's a metadata layer on data, wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud, up until this point. So it's effectively an extension of that functionality into the Dell On-Premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake. So that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> So as Clark explained, this capability of External tables has been around in the Cloud for a while, mainly to suck data out of Cloud data lakes. Snowflake External Tables use file level metadata, for instance, the name of the file and the versioning so that it can be queried in a stage. A stage is just an external location outside of Snowflake. It could be an S3 bucket or an Azure Blob and it's soon will be a Dell object store. And in using this feature, the Dell looks like it lives inside of Snowflake and Clark essentially, he's correct to say to an analyst that looks exactly like the data is in Snowflake, but uh, not exactly the data's read only which means you can't do what are called DML operations. DML stands for Data Manipulation Language and allows for things like inserting data into tables or deleting and modifying existing data. But the data can be queried. However, the performance of those queries to External Tables will almost certainly be slower. Now users can build things like materialized views which are going to speed things up a bit, but at the end of the day, it's going to run faster than the Cloud. And you can be almost certain that's where Snowflake wants it to run, but some organizations can't or won't move data into the Cloud for a variety of reasons, data sovereignty, compliance security policies, culture, you know, whatever. So data can remain in place On-prem, or it can be moved into the Public Cloud with this new announcement. Now, the compute today presumably is going to be done in the Public Cloud. I don't know where else it's going to be done. They really didn't talk about the compute side of things. Remember, one of Snowflake's early innovations was to separate compute from storage. And what that gave them is you could more efficiently scale with unlimited resources when you needed them. And you could shut off the compute when you don't need us. You didn't have to buy, and if you need more storage you didn't have to buy more compute and vice versa. So everybody in the industry has copied that including AWS with Redshift, although as we've reported not as elegantly as Snowflake did. RedShift's more of a storage tiering solution which minimizes the compute required but you can't really shut it off. And there are companies like Vertica with Eon Mode that have enabled this capability to be done On-prem, you know, but of course in that instance you don't have unlimited elastic compute scale on-Prem but with solutions like Dell Apex and HPE GreenLake, you can certainly, you can start to simulate that Cloud elasticity On-prem. I mean, it's not unlimited but it's sort of gets you there. According to a Dell Snowflake joint statement, the companies the quote, the companies will pursue product integrations and joint go to market efforts in the second half of 2022. So that's a little vague and kind of benign. It's not really clear when this is going to be available based on that statement from the two first, but, you know, we're left wondering will Dell develop an On-Prem compute capability and enable queries to run locally maybe as part of an extended apex offering? I mean, we don't know really not sure there's even a market for that but it's probably a good bet that again, Snowflake wants that data to land in the Snowflake data Cloud kind of makes you wonder how this deal came about. You heard Sloop on earlier Snowflake has always been pretty dogmatic about getting data into its native snowflake format to enable the best performance as we talked about but also data sharing and governance. But you could imagine that data architects they're building out their data mesh we've reported on this quite extensively and their data fabric and those visions around that. And they're probably telling Snowflake, Hey if you want to be a strategic partner of ours you're going to have to be more inclusive of our data. That for whatever reason we're not putting in your Cloud. So Snowflake had to kind of hold its nose and capitulate. Now the good news is it further opens up Snowflakes Tam the total available market. It's obviously good marketing posture. And ultimately it provides an on ramp to the Cloud. And we're going to come back to that shortly but let's look a little deeper into what's happening with data platforms and to do that we'll bring in some ETR data. Now, let me just say as companies like Dell, IBM, Cisco, HPE, Lenovo, Pure and others build out their hybrid Clouds. The cold hard fact is not only do they have to replicate the Cloud Operating Model. You will hear them talk about that a lot, but they got to do that. So it, and that's critical from a user experience but in order to gain that flywheel momentum they need to build a robust ecosystem that goes beyond their proprietary portfolios. And, you know, honestly they're really not even in the first inning most companies and for the likes of Snowflake to sort of flip this, they've had to recognize that not everything is moving into the Cloud. Now, let's bring up the next slide. One of the big areas of discussion at Dell Tech World was Apex. That's essentially Dell's nascent as a service offering. Apex is infrastructure as a Service Cloud On-prem and obviously has the vision of connecting to the Cloud and across Clouds and out to the Edge. And it's no secret that database is one of the most important ingredients of infrastructure as a service generally in Cloud Infrastructure specifically. So this chart here shows the ETR data for data platforms inside of Dell accounts. So the beauty of ETR platform is you can cut data a million different ways. So we cut it. We said, okay, give us the Cloud platforms inside Dell accounts, how are they performing? Now, this is a two dimensional graphic. You got net score or spending momentum on the vertical axis and what ETR now calls Overlap formally called Market Share which is a measure of pervasiveness in the survey. That's on the horizontal axis that red dotted line at 40% represents highly elevated spending on the Y. The table insert shows the raw data for how the dots are positioned. Now, the first call out here is Snowflake. According to ETR quote, after 13 straight surveys of astounding net scores, Snowflake has finally broken the trend with its net score dropping below the 70% mark among all respondents. Now, as you know, net score is measured by asking customers are you adding the platform new? That's the lime green in the bar that's pointing from Snowflake in the graph and or are you increasing spend by 6% or more? That's the forest green is spending flat that's the gray is you're spend decreasing by 6% or worse. That's the pinkish or are you decommissioning the platform bright red which is essentially zero for Snowflake subtract the reds from the greens and you get a net score. Now, what's somewhat interesting is that snowflakes net score overall in the survey is 68 which is still huge, just under 70%, but it's net score inside the Dell account base drops to the low sixties. Nonetheless, this chart tells you why Snowflake it's highly elevated spending momentum combined with an increasing presence in the market over the past two years makes it a perfect initial data platform partner for Dell. Now and in the Ford versus Ferrari dynamic. That's going on between the likes of Dell's apex and HPE GreenLake database deals are going to become increasingly important beyond what we're seeing with this recent Snowflake deal. Now noticed by the way HPE is positioned on this graph with its acquisition of map R which is now part of HPE Ezmeral. But if these companies want to be taken seriously as Cloud players, they need to further expand their database affinity to compete ideally spinning up databases as part of their super Clouds. We'll come back to that that span multiple Clouds and include Edge data platforms. We're a long ways off from that. But look, there's Mongo, there's Couchbase, MariaDB, Cloudera or Redis. All of those should be on the short list in my view and why not Microsoft? And what about Oracle? Look, that's to be continued on maybe as a future topic in a, in a Breaking Analysis but I'll leave you with this. There are a lot of people like John Furrier who believe that Dell is playing with fire in the Snowflake deal because he sees it as a one way ticket to the Cloud. He calls it a one way door sometimes listen to what he said this past week. >> I would say that that's a dangerous game because we've seen that movie before, VMware and AWS. >> Yeah, but that we've talked about this don't you think that was the right move for VMware? >> At the time, but if you don't nurture the relationship AWS will take all those customers ultimately from VMware. >> Okay, so what does the data say about what John just said? How is VMware actually doing in Cloud after its early missteps and then its subsequent embracing of AWS and other Clouds. Here's that same XY graphic spending momentum on the Y and pervasiveness on the X and the same table insert that plots the dots and the, in the breakdown of Dell's net score granularity. You see that at the bottom of the chart in those colors. So as usual, you see Azure and AWS up and to the right with Google well behind in a distant third, but still in the mix. So very impressive for Microsoft and AWS to have both that market presence in such elevated spending momentum. But the story here in context is that the VMware Cloud on AWS and VMware's On-Prem Cloud like VMware Cloud Foundation VCF they're doing pretty well in the market. Look, at HPE, gaining some traction in Cloud. And remember, you may not think HPE and Dell and VCF are true Cloud but these are customers answering the survey. So their perspective matters more than the purest view. And the bad news is the Dell Cloud is not setting the world on fire from a momentum standpoint on the vertical axis but it's above the line of zero and compared to Dell's overall net score of 20 you could see it's got some work to do. Okay, so overall Dell's got a pretty solid net score to you know, positive 20, as I say their Cloud perception needs to improve. Look, Apex has to be the Dell Cloud brand not Dell reselling VMware. And that requires more maturity of Apex it's feature sets, its selling partners, its compensation models and it's ecosystem. And I think Dell clearly understands that. I think they're pretty open about that. Now this includes partners that go beyond being just sellers has to include more tech offerings in the marketplace. And actually they got to build out a marketplace like Cloud Platform. So they got a lot of work to do there. And look, you've got Oracle coming up. I mean they're actually kind of just below the magic 40% in the line which is pro it's pretty impressive. And we've been telling you for years, you can hate Oracle all you want. You can hate its price, it's closed system all of that it's red stack shore. You can say it's legacy. You can say it's old and outdated, blah, blah, blah. You can say Oracle is irrelevant in trouble. You are dead wrong. When it comes to mission critical workloads. Oracle is the king of the hill. They're a founder led company that knows exactly what it's doing and they're showing Cloud momentum. Okay, the last point is that while Microsoft AWS and Google have major presence as shown on the X axis. VMware and Oracle now have more than a hundred citations in the survey. You can see that on the insert in the right hand, right most column. And IBM had better keep the momentum from last quarter going, or it won't be long before they get passed by Dell and HP in Cloud. So look, John might be right. And I would think Snowflake quietly agrees that this Dell deal is all about access to Dell's customers and their data. So they can Hoover it into the Snowflake Data Cloud but the data right now, anyway doesn't suggest that's happening with VMware. Oh, by the way, we're keeping an eye close eye on NetApp who last September ink, a similar deal to VMware Cloud on AWS to see how that fares. Okay, let's wrap with some closing thoughts on what this deal means. We learned a lot from the Cloud generally in AWS, specifically in two pizza teams, working backwards, customer obsession. We talk about flywheel all the time and we've been talking today about marketplaces. These have all become common parlance and often fundamental narratives within strategic plans investor decks and customer presentations. Cloud ecosystems are different. They take both competition and partnerships to new heights. You know, when I look at Azure service offerings like Apex, GreenLake and similar services and I see the vendor noise or hear the vendor noise that's being made around them. I kind of shake my head and ask, you know which movie were these companies watching last decade? I really wish we would've seen these initiatives start to roll out in 2015, three years before AWS announced Outposts not three years after but Hey, the good news is that not only was Outposts a wake up call for the On-Prem crowd but it's showing how difficult it is to build a platform like Outposts and bring it to On-Premises. I mean, Outpost isn't currently even a rounding era in the marketplace. It really doesn't do much in terms of database support and support of other services. And, you know, it's unclear where that that is going. And I don't think it has much momentum. And so the Hybrid Cloud Vendors they've had time to figure it out. But now it's game on, companies like Dell they're promising a consistent experience between On-Prem into the Cloud, across Clouds and out to the Edge. They call it MultCloud which by the way my view has really been multi-vendor Chuck, Chuck Whitten. Who's the new co-COO of Dell called it Multi-Cloud by default. (laughing) That's really, I think an accurate description of that. I call this new world Super Cloud. To me, it's different than MultiCloud. It's a layer that runs on top of hyperscale infrastructure kind of hides the underlying complexity of the Cloud. It's APIs, it's primitives. And it stretches not only across Clouds but out to the Edge. That's a big vision and that's going to require some seriously intense engineering to build out. It's also going to require partnerships that go beyond the portfolios of companies like Dell like their own proprietary stacks if you will. It's going to have to replicate the Cloud Operating Model and to do that, you're going to need more and more deals like Snowflake and even deeper than Snowflake, not just in database. Sure, you'll need to have a catalog of databases that run in your On-Prem and Hybrid and Super Cloud but also other services that customers can tap. I mean, can you imagine a day when Dell offers and embraces a directly competitive service inside of apex. I have trouble envisioning that, you know not with their historical posture, you think about companies like, you know, Nutanix, you know, or Cisco where they really, you know those relationships cooled quite quickly but you know, look, think about it. That's what AWS does. It offers for instance, Redshift and Snowflake side by side happily and the Redshift guys they probably hate Snowflake. I wouldn't blame them, but the EC Two Folks, they love them. And Adam SloopesKy understands that ISVs like Snowflake are a key part of the Cloud ecosystem. Again, I have a hard time envisioning that occurring with Dell or even HPE, you know maybe less so with HPE, but what does this imply that the Edge will allow companies like Dell to a reach around on the Cloud and somehow create a new type of model that begrudgingly accommodates the Public Cloud but drafts of the new momentum of the Edge, which right now to these companies is kind of mostly telco and retail. It's hard to see that happening. I think it's got to evolve in a more comprehensive and inclusive fashion. What's much more likely is companies like Dell are going to substantially replicate that Cloud Operating Model for the pieces that they own pieces that they control which admittedly are big pieces of the market. But unless they're able to really tap that ecosystem magic they're not going to be able to grow much beyond their existing install bases. You take that lime green we showed you earlier that new adoption metric from ETR as an example, by my estimates, AWS and Azure are capturing new accounts at a rate between three to five times faster than Dell and HPE. And in the more mature US and mere markets it's probably more like 10 X and a major reason is because of the Cloud's robust ecosystem and the optionality and simplicity of transaction that that is bringing to customers. Now, Dell for its part is a hundred billion dollar revenue company. And it has the capability to drive that kind of dynamic. If it can pivot its partner ecosystem mindset from kind of resellers to Cloud services and technology optionality. Okay, that's it for now? Thanks to my colleagues, Stephanie Chan who helped research topics for Breaking Analysis. Alex Myerson is on the production team. Kristen Martin and Cheryl Knight and Rob Hof, on editorial they helped get the word out and thanks to Jordan Anderson for the new Breaking Analysis branding and graphics package. Remember these episodes are all available as podcasts wherever you listen. All you do is search Breaking Analysis podcasts. You could check out ETR website @etr.ai. We publish a full report every week on wikibon.com and siliconangle.com. You want to get in touch. @dave.vellente @siliconangle.com. You can DM me @dvellante. You can make a comment on our LinkedIn posts. This is Dave Vellante for the Cube Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (upbeat music)

>> Narrator: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi, and welcome to this CUBE conversation, I'm Stu Min and I'm coming to you from our Boston area studio, we've been digging in with the Pensando team, understand how they're fitting into the cloud, multi-cloud, edge discussion, really thrilled to welcome to the program, first time guest, Silvano Gai, he's a fellow with Pensando. Silvano, really nice to see you again, thanks so much for joining us on theCUBE. >> Stuart, it's so nice to see you, we used to work together many years ago and that was really good and is really nice to come to you from Oregon, from Bend, Oregon. A beautiful town in the high desert of Oregon. >> I do love the Pacific North West, I miss the planes and the hotels, I should say, I don't miss the planes and the hotels, but going to see some of the beautiful places is something I do miss and getting to see people in the industry I do like. As you mentioned, you and I crossed paths back through some of the spin-ins, back when I was working for a very large storage company, you were working for SISCO, you were known for writing the book, you were a professor in Italy, many of the people that worked on some of those technologies were your students. But Silvano, my understanding is you retired so, maybe share for our audience, what brought you out of that retirement and into working once again with some of your former colleagues and on the Pensando opportunity. >> I did retire for a while, I retired in 2011 from Cisco if I remember correctly. But at the end of 2016, beginning of 2017, some old friend that you may remember and know called me to discuss some interesting idea, which was basically the seed idea that is behind the Pensando product and their idea were interesting, what we built, of course, is not exactly the original idea because you know product evolve over time, but I think we have something interesting that is adequate and probably superb for the new way to design the data center network, both for enterprise and cloud. >> All right, and Silvano, I mentioned that you've written a number of books, really the authoritative look on when some new products had been released before. So, you've got a new book, "Building a Future-Proof Cloud Infrastructure," and look at you, you've got the physical copy, I've only gotten the soft version. The title, really interesting. Help us understand how Pensando's platform is meeting that future-proof cloud infrastructure that you discuss. >> Well, network have evolved dramatically in the data center and in the cloud. You know, now the speed of classical server in enterprise is probably 25 gigabits, in the cloud we are talking of 100 gigabit of speed for a server, going to 200 gigabit. Now, the backbone are ridiculously fast. We no longer use Spanning Tree and all the stuff, we no longer use access code aggregation. We switched to closed network, and with closed network, we have huge enormous amount of bandwidth and that is good but it also imply that is not easy to do services in a centralized fashion. If you want to do a service in a centralized fashion, what you end up doing is creating a giant bottleneck. You basically, there is this word that is being used, that is trombone or tromboning. You try to funnel all this traffic through the bottleneck and this is not really going to work. The only place that you can really do services is at the edge, and this is not an invention, I mean, even all the principles of cloud is move everything to the edge and maintain the network as simple as possible. So, we approach services with the same general philosophy. We try to move services to the edge, as close as possible to the server and basically at the border between the sever and the network. And when I mean services I mean three main categories of services. The networking services of course, there is the basic layer, two-layer, three stuff, plus the bonding, you know VAMlog and what is needed to connect a server to a network. But then there is the overlay, overlay like the xLAN or Geneva, very very important, basically to build a cloud infrastructure, and that are basically the network service. We can have others but that, sort of is the core of a network service. Some people want to run BGP layers, some people don't want to run BGP. There may be a VPN or kind of things like that but that is the core of a network service. Then of course, and we go back to the time we worked together, there are storage services. At that time, we were discussing mostly about fiber tunnel, now the BUS world is clearly NVMe, but it's not just the BUS world, it's really a new way of doing storage, and is very very interesting. So, NVMe kind of service are very important and NVMe as a version that is called NVMeOF, over fiber. Which is basically, sort of remote version of NVMe. And then the third, least but not last, most important category probably, is security. And when I say that security is very very important, you know, the fact that security is very important is clear to everybody in our day, and I think security has two main branches in terms of services. There is the classical firewall and micro-segmentation, in which you basically try to enforce the fact that only who is allowed to access something can access something. But you don't, at that point, care too much about the privacy of the data. Then there is the other branch that encryption, in which you are not trying to enforce to decide who can access or not access the resource, but you are basically caring about the privacy of the data, encrypting the data so that if it is hijacked, snooped or whatever, it cannot be decoded. >> Eccellent, so Silvano, absolutely the edge is a huge opportunity. When someone looks at the overall solution and say you're putting something in the edge, you know, they could just say, "This really looks like a NIC." You talked about some of the previous engagement we'd worked on, host bus adapters, smart NICs and the like. There were some things we could build in but there were limits that we had, so, what differentiates the Pensando solution from what we would traditionally think of as an adapter card in the past? >> Well, the Pensando solution has two main, multiple pieces but in term of hardware, has two main pieces, there is an ASIC that we call copper internally. That ASIC is not strictly related to be used only in an adapter form, you can deploy it also in other form factors in another part of the network in other embodiment, et cetera. And then there is a card, the card has a PCI-E interface and sit in a PCI-E slot. So yes, in that sense, somebody can can call it a NIC and since it's a pretty good NIC, somebody can call it a smart NIC. We don't really like that two terms, we prefer to call it DSC, domain specific card, but the real term that I like to use is domain specific hardware, and I like to use domain specific hardware because it's the same term that Hennessy and Patterson use in a beautiful piece of literature that is the Turing Award lecture. It's on the internet, it's public, I really ask everybody to go and try to find it and listen to that beautiful piece of literature, modern literature on computer architecture. The Turing Award lecture of Hennessy and Patterson. And they have introduced the concept of domain specific hardware, and they explain also the justification for why now is important to look at domain specific hardware. And the justification is basically in a nutshell and we can go more deep if you're interested, but in a nutshell is that the specing, that is the single tried performer's measurement of a CPU, is not growing fast at all, is only growing nowadays like a few point percent a year, maybe 4% per year. And with this slow grow, over specing performance of a core, you know the core need to be really used for user application, for customer application, and all what is known as Sentian can be moved to some domain specific hardware that can do that in a much better fashion, and by no mean I imply that the DSC is the best example of domain specific hardware. The best example of domain specific hardware is in front of all of us, and are GPUs. And not GPUs for graphic processing which are also important, but GPU used basically for artificial intelligence, machine learning inference. You know, that is a piece of hardware that has shown that something can be done with performance that the purpose processor can do. >> Yeah, it's interesting right. If you term back the clock 10 or 15 years ago, I used to be in arguments, and you say, "Do you build an offload, "or do you let it happen is software." And I was always like, "Oh, well Moore's law with mean that, "you know, the software solution will always win, "because if you bake it in hardware, it's too slow." It's a very different world today, you talk about how fast things speed up. From your customer standpoint though, often some of those architectural things are something that I've looked for my suppliers to take care of that. Speak to the use case, what does this all mean from a customer stand point, what are some of those early use cases that you're looking at? >> Well, as always, you get a bit surprised by the use cases, in the sense that you start to design a product thinking that some of the most cool thing will be the dominant use cases, and then you discover that something that you have never really fought have the most interesting use case. One that we have fought about since day one, but it's really becoming super interesting is telemetry. Basically, measuring everything in the network, and understanding what is happening in the network. I was speaking with a friend the other day, and the friend was asking me, "Oh, but we have SNMP for many many years, "which is the difference between SNMP and telemetry?" And the difference is to me, the real difference is in SNMP or in many of these management protocol, you involve a management plan, you involve a control plan, and then you go to read something that is in the data plan. But the process is so inefficient that you cannot really get a huge volume of data, and you cannot get it practically enough, with enough performance. Doing telemetry means thinking a data path, building a data path that is capable of not only measuring everything realtime, but also sending out that measurement without involving anything else, without involving the control path and the management path so that the measurement becomes really very efficient and the data that you stream out becomes really usable data, actionable data in realtime. So telemetry is clearly the first one, is important. One that you honestly, we had built but we weren't thinking this was going to have so much success is what we call Bidirectional ERSPAN. And basically, is just the capability of copying data. And sending data that the card see to a station. And that is very very useful for replacing what are called TAP network, Which is just network, but many customer put in parallel to the real network just to observe the real network and to be able to troubleshoot and diagnose problem in the real network. So, this two feature telemetry and ERSPAN that are basically troubleshooting feature are the two features that are beginning are getting more traction. >> You're talking about realtime things like telemetry. You know, the applications and the integrations that you need to deal with are so important, back in some of the previous start-ups that you done was getting ready for, say how do we optimize for virtualization, today you talk cloud-native architectures, streaming, very popular, very modular, often container based solutions and things change constantly. You look at some of these architectures, it's not a single thing that goes on for a long period of time, but it's lots of things that happen over shorter periods of time. So, what integrations do you need to do, and what architecturally, how do you build things to make them as you talk, future-proof for these kind of cloud architectures? >> Yeah, what I mentioned were just the two low hanging fruit, if you want the first two low hanging fruit of this architecture. But basically, the two that come immediately after and where there is a huge amount of radio are distributor's state for firewall, with micro-segmentation support. That is a huge topic in itself. So important nowadays that is absolutely fundamental to be able to build a cloud. That is very important, and the second one is wire rate encryption. There is so much demand for privacy, and so much demand to encrypt the data. Not only between data center but now also inside the data center. And when you look at a large bank for example. A large bank is no longer a single organization. A large bank is multiple organizations that are compartmentalized by law. That need to keep things separate by law, by regulation, by FCC regulation. And if you don't have encryption, and if you don't have distributed firewall, is really very difficult to achieve that. And then you know, there are other applications, we mentioned storage NVME, and is a very nice application, and then we have even more, if you go to look at load balance in between server, doing compression for storage and other possible applications. But I sort of lost your real question. >> So, just part of the pieces, when you look at integrations that Pensando needs to do, for maybe some of the applications that you would tie in to any of those that come to mind? >> Yeah, well for sure. It depends, I see two main branches again. One is the cloud provider, and one are the enterprise. In the cloud provider, basically this cloud provider have a huge management infrastructure that is already built and they want just the card to adapt to this, to be controllable by this huge management infrastructure. They already know which rule they want to send to the card, they already know which feature they want to enable on the card. They already have all that, they just want the card to provide the data plan performers for that particular feature. So they're going to build something particular that is specific for that particular cloud provider that adapt to that cloud provider architecture. We want the flexibility of having an API on the card that is like a rest API or a gRPC which they can easily program, monitor and control that card. When you look at the enterprise, the situation is different. Enterprise is looking to at two things. Two or three things. The first thing is a complete solution. They don't want to, they don't have the management infrastructure that they have built like a cloud provider. They want a complete solution that has the card and the management station and there's all what is required to make from day one, a working solution, which is absolutely correct in an enterprise environment. They also want integration, and integration is the tool that they already have. If you look at main enterprise, one of a dominant presence is clearly VMware virtualization in terms of ESX and vSphere and NSX. And so most of the customer are asking us to integrate with VMware, which is a very reasonable demand. And then of course, there are other player, not so much in the virtualization's space, but for example, in the data collections space, and the data analysis space, and for sure Pensando doesn't want to reinvent the wheel there, doesn't want to build a data collector or data analysis engine and whatever, there is a lot of work, and there are a lot out there, so integration with things like Splunk for example are kind of natural for Pensando. >> Eccellent, so wait, you talked about some of the places where Pensando doesn't need to reinvent the wheel, you talk through a lot of the different technology pieces. If I had to have you pull out one, what would you say is the biggest innovation that Pensando has built into the platform. >> Well, the biggest innovation is this P4 architecture. And the P4 architecture was a sort of gift that was given us in the sense that it was not invented for what we use it. P4 was basically invented to have programmable switches. The first big P4 company was clearly Barefoot that then was acquired by Intel and Barefoot built a programmable switch. But if you look at the reality of today, the network, most of the people want the network to be super easy. They don't want to program anything into the network. They want to program everything at the edge, they want to put all the intelligence and the programmability of the edge, so we borrowed the P4 architecture, which is fantastic programmable architecture and we implemented that yet. It's also easier because the bandwidth is clearly more limited at the edge compared to being in the core of a network. And that P4 architecture give us a huge advantage. If you, tomorrow come up with the Stuart Encapsulation Super Duper Technology, I can implement in the copper The Stuart, whatever it was called, Super Duper Encapsulation Technology, even when I design the ASIC I didn't know that encapsulation exists. Is the data plan programmability, is the capability to program the data plan and programming the data plan while maintaining wire-speed performance, which I think is the biggest benefit of Pensando. >> All right, well Silvano, thank you so much for sharing, your journey with Pensando so far, really interesting to dig into it and absolutely look forward to following progress as it goes. >> Stuart, it's been really a pleasure to talk with you, I hope to talk with you again in the near future. Thank you so much. >> All right, and thank you for watching theCUBE, I'm Stu Miniman, thanks for watching. (upbeat music)

it's the cube covering vmworld 2015 brought to you by VMware and its ecosystem sponsors and now your host dave vellante welcome back to moscone center everybody this is the cube silicon angles continuous production of vmworld 2015 Brian biles is here he's the CEO and co-founder of day trium Brian of course from data domain Fame David floor and I are really excited to see you thanks for coming on the cue that's great to see you guys again so in a while coming out of stealth right it's been a while you've been you've been busy right you get a domain work the DMC for a while kind of disappeared got really busy again and here you are yeah new hats got new books yeah yeah so tell us about daydream fundamentally guys on time yeah yeah well we're big on ties on the East Coast are you too well he's even more east than I am even though he goes out in California but uh yeah tell us about date you fundamentally different fundamentally different from other kinds of storage different kind of founding team so I was a founder of data domain and Hugo Patterson the CTO there BMC fellow became CTO for us we hadn't when we left emc we weren't sure what we were going to do we end up running into to VMware principal engineers who had been there 10 or 12 years working on all kinds of stuff and they believed that there was a market gap on scalable storage for VMS so we got together we use something about storage they knew something about BMS and three years later date reham is at its first trade show so talk more about that that Gavin happens all the time right guys alpha geeks nah no offense to that term it's a term of endearment yea sorry I'm a marketing guy tech ghastly ok so they get together and they sort of identify these problems and they're able to sniff them out at the root level so what really can you describe that problem or detail sure so broadly there are two kinds of storage right there's sort of arrays and emerging there's hyper converge they approach things in a very different way in a raise there tends to be a bottleneck in the controller the the electronics that that do the data services this the raid and the snapshotting and cloning and compression indeed even whatever and increasingly that takes more and more compute so Intel is you know helping every year but it's still a bottleneck and when you run out it's a cliff and you have to do a pretty expensive upgrade or migrate the data to a different place and that's sticky and takes a long time so in reaction hyper converged has emerged as an alternative and it you know it has the benefit of killing the array completely but it may have over corrected so it has some trade-offs that a lot of people don't like for example if a host goes down you know the host has assumed all the data management problems that are raised used to have so you have to migrate the data or rebuild it to service the hose if you know you can't have a fit very cleanly between a for example a blade server which has one or two drive bays and a hyper converged model where you know you look across the floor the sort of average number of capacity drives is four or five not to mention the cache drives so a blade server it's just not a fit so there's a lot of parts of the industry where that model is just not the right model you know if everybody is writing to everybody then there's a lot of neighbor noise it gets kind of weird to troubleshoot in tune arrays you know we're better in some respects things change with hyper converged a little different we're trying to create a third path in our model there's a box that we sell it's a 2u rackmount a bunch of drives for capacity but the capacity is just for at rest data it's where all the rights go it's where persistence goes but we move all the data service processing the CPU for raid for compression for dee doop whatever to host cycles we upload software to an ESX host and it uses you know anybody's x86 server and you bring your own flash for caching so you know Gartner did a thing at the end of the year where they looked at discounted street price for flash the difference between what you could pay on a server for flash you know just a commodity SSD and what you could pay in an array it was like an 8x difference so if you don't you know we don't put raid on the host all the rate is in the back end so that frees up another whatever twenty percent you end up getting an order of magnitude difference in pricing so what you can get from us in flash on a host is not you don't aim at ten percent you know of your active data in cash it gets close to a hundred dollars a terabyte after you do d Dupin compression on you know server flash so it's just cheap and plentiful you put all your data up there everything runs out of flash locally it never gets a network hit for a read we do read caching locally unlike a hyper converge we don't spread data in a pool across the host we're not interrupting every host for read for rights for you know somebody else everything is local so when you do a write it goes to our box on the end of the wire 10 gig attached but all of the compute operations are local so you're not interrupting everybody all the resourcing you would do for any i/o problem is a local either cores or flash resourcing so it's a different model and it you know it's a really well student from blade servers no one else was doing that in such a good way unlike a cash-only product it's completely organically designed for manageability you don't have a separate tier for managing on the host separate from an array where you know you're probably duplicating provisioning and having to worry about how to do dinner a snapshot when you have to flush the cache on the host it's all completely designed from the ground up so it means the the storage that we store too is minimal cost we don't have the compute overhead that you have with a controller you don't have the flash which is really expensive there that's just cycles on the host everything is you know done with the most efficient path for both data and hardware so if you look at designs in general the flash is either being a cache or it's been 100% flash or it's been a tier of story so you're just fine understand that correctly there isn't any tearing because you've got a hundred percent of it in flash so that your goals yeah we use flash on the host as a cash right but only in the sort of i only use that word guardedly initial degenerate case it's all of the data yeah so it's a cash in the spirit that if the coast dies you haven't lost any data the data is always safe somewhere else right but it's all the data it's all the data so that's sitting on the disk the back end I presume you're writing sequential event all the time with log files answering and you saw the the disk in the most effective way that's right at both sides move the flash it's a log structured and the disk it's a log stretch ownership yeah and you know we had the advantage of data domain it was the most popular log structured file system ever and you know we learned all the tricks about dee doop and garbage collection along time ago so that CTO team is uniquely qualified to get this right so what about if it does go down are you clustering it what happens when it goes down and you have to recover from those disk drives that could take a bit of time good so there's two sides of that if a host fails you know you you use vm h a to restart the vm somewhere else and life goes on if the back end fails it fails the way a traditional mid-range array might fail we have dual controllers so stay over there all the disks are dual attached there's you know dual networks on each controller you can have service which failover it's a raid 6 so there's a rebuild that happens if it disk fails but you could have two of those and keep going but a point i was getting it was that if you fail in the host you've lost all your active data be precise with them we've lost the cache copy in that local flash but you haven't lost any de una lista de menthe you've lost it from the point of view of the only from a standpoint of speed yeah so at that point you know if the ho is down you have to restart the vm somewhere else that's not instant that takes number of minutes and that gives us some time to upload data to that host to know that great good the data is all laid out in our system not for interactive views on the disk drives but for very fast upload to a cash right it's all sort of sequentially laid out unblended per vm for blasting too so what do you see is the key application times that this is going to be particularly suited full so we have the our back-end system has about 30 terabytes usable after all the you know raid and everything and dude even compressions so I figure you know 2 4 6 X data reduction call it 100 terabytes ish depends on mileage so 100 terabyte box will you know sell that that's kind of a mid-range class array it will sell mostly to those markets and our software supports only vm storage virtual disks so as long as it meets those criteria it's pretty flexible the host each host can have up to eight terabytes of raw flash you know post d doofen compression that could be 50 terabytes of effective capacity of flash / host and you know reads never leave the host so you don't get network overhead for read so that's usually two-thirds of most people I own so it's enormously price and cost effective and very performance performant as well right right latency stuff and your IP is the way you lay out the data on the media is that part of the well listen it's it's like to custom file systems from scratch yeah once in one of the hosts not to mention all the management to make it look like there's one thing you know so it's there's a lot going on it's a much more complex project than data domain wise yeah so you mentioned you know you learned from your blog structured file garbage collection days of data but the the problem that you're solving here is much closer to the host much more active data so was that obviously a challenge but so that was part of the new invention required or was really just directly sort of i mean it's at all levels we had to make it fit so we're very vm centric it looks to the software looks to ESX as though it's an NFS share right but NFS terminates in each host and then we use our own protocol to get across 10 gig to the backend and this gives us some special effects will be able to talk about overtime every version alike at entry design in some ways well it's an offense so so you get to see every VMs storage discreetly it's sort of a you know before v vols there was NFS what many support five dot five so this was a logical choice right so everything's vm centric all of the management just it just looks like there's a big pool of storage and everything else is per vm from from diagnostics to capacity planning to whatever clones are per vm you don't have to you know spend a lot of analytics to fig you know back out what the block Lunds look like with respect to the VMS and try to you know look it up figured out it's just that's all there is so I've talked to a lot of we keep on been talking to a lot of flash and you people and this is almost a flash only in the sense that you are everything is going all of the idea is going to that flash once flash is sufficiently cheap and abundant yes no so and we know we write to nvram which is the same as an all-flash array so one of the things that we've noticed is that what they find is that they have to organize things completely differently particularly as they're trying to share things and for example instead of having a the production system and then a separate copy for each application developer another separate coffee for the for the data warehouse they're trying to combine those and share the data across there with snapshots of one sort or knowledge to amortize they're very high costs just because it's much faster and quicker since the customers are doing this and I think you're not they did vendors they don't even know what's going on so but because they can share it you don't have to move the data well so it's good it's allows the developers have a more current copy the data so they can work on near production all right yeah so I was just wondering whether that was an area that you are looking at to again apply a different way of doing storage so it takes a test debuts case you saying yeah well testing or data warehousing or whatever I mean we're certainly sensitive to the overhead of having a lot of copies that's why you insolent Dean you and so on the way we do so it's but you can get so very efficient but it allows you to for example if you're doing a clone it's a you know a dee doo clone so it's it gives you a new name space entry and it keeps the rights separate but it it you know lets the common data the data with commonality across other versions be consistent so we gotta wrap but the time we have remaining so just quick update on the company headcount funding investors maybe just give us the rundown sure we raised Series A and B we've raised about 55 million so far NEA and light speed plus some angels Frank's luqman Kylie Diane Greene original founder of VMware and Ed Boon yan who was the original CTO right about a little over 70 people great and this is our first trade show and yeah awesome well congratulations Brian you know it's really awesome to see you back in and actually not to have been in action but now invisible action so well it's great to be here thanks very much for coming on cue congrat day everybody will be back right after this is the cube rely from vmworld 2015 right back