(upbeat music) >> Okay, welcome back, everyone, it's CUBE's live coverage. I'm John Furrier, host of theCUBE here with Paul Gillen. Got a great guest coming up here, talking about cloud security, all things going on in the cloud. Paul, great day. How you doing? How you holding up? >> I'm about at the end of my, running on fumes, John. (John laughs) >> Let's bring it home. >> And we got another day coming up. >> Day three, let's bring it home, come on, let's go. Lot of energy. >> Lot of energy on the floor and certainly a lot of talk about security at this conference. Busy, busy market, lots of vendors. And one of the more notable ones, Cohesity, recently introduced a brand new suite, a brand new approach to security that combines data protection and security and backup. With us, to talk about that is Amith Nair, who is the Senior Vice president and General Manager of cloud at Cohesity. Welcome. >> Thank you very much. Thanks for having me, Paul and John. >> So tell us about DataHawk, your new product. >> Yeah, just to set a little bit of perspective on Cohesity, and how we think about DataHawk and security in general is, Cohesity is the leading solution for data security and management. And if you think about all the pillars that we provide in terms of solution around that data solutions, so we have data protection, data security, data access, data mobility and data insights. So the focus for us over the last many months was really to make our data security solutions really strong. So generally when customers think about security, they think about starting with security at the perimeter, on the edge. They think about firewalls, network layer, and so on and so forth. But in the end, what they're really trying to protect is the data that aligns to what they're really trying to save. Right? So DataHawk was formulated and built in order to help extend our existing solutions to provide additional security, layers of security, and also work with partners to enable doing that. Many months ago, we released this product called FortKnox, which is our cyber vaulting solution. One that customers really love and use today. >> It's an air gap solution, right? >> It's an air gap solution with forum capabilities, and so on. Extremely liked by customers, very well adopted, and we extended that to provide lots more data classification capabilities, and ransomware checks as well. So malware checks in the product itself in terms of what it is being backed up. And is there malware in the backed up data and so on? >> Maybe, we can talk about the evolution of ransomware, because ransomware is getting a lot more sophisticated. It used to start at the end point and then penetrate into the network. Increasingly, now, we're seeing it move into the backup, and actually corrupt backup files before moving into the production data. How is ransomware evolving? >> I mean, there's a ransomware attack that's happening right now as we speak, right? What is it? One in every 11 seconds or so on. And it's getting very, very sophisticated. And you're absolutely right, the target early on used to be the network, or the firewall and so on and so forth. Now, it is the backup. So you have to be very smart about how you protect your backup and if you do get attacked, which a lot of CSOs are starting to realize, it's not about just preventing. But it's also what do you do if it does happen? How can you be resilient in the case of an attack? How can you recover if something happens? And that's where we come in to play as well. >> What's some of the state of the art posture, security posture and cyber resilient techniques? Can you share your observations on what are some of the current state of the art positions? I mean, besides they buy everything, and they want everything, but we're looking at a cost reduction, slow down in the recession, customer's going to look at belt tightening. We heard that from Adam Celeste. Has that changed or enhanced the posture, and impact to the resiliency on the cyber side? >> Yeah, I think customers are getting really smart in terms of how they're adopting cloud. We saw a tremendous amount of growth from a cloud usage perspective, I think, over the last two years and through the pandemic. But now they're getting smart about, "How am I consuming that cloud?" Which is where the consumption's starting to slow down. But that does not mean they're not using cloud, right? And security from a cloud perspective is way different from the old world, which was very static. You're in a completely dynamic environment now. So everybody talks about zero trust security. You have to have that level of no trust, trust nothing, authenticate everything, in terms of how you approach what connects to your network, what services connect to your network and so on. And we follow the same approach, but we also believe that one solution cannot solve it. And which is why we had this announcement around our security advisory council, and security partnership and alliances, where we are providing data to additional solutions, or insights into other security solutions that will help the customer in the end. We talked about how some customers have anywhere between 50 to 70 vendors on their network for security. We want to reduce that noise and that clutter, especially when it comes to cost and expenses. Right? >> Awesome. I want to ask you a personal question if you don't mind. You're new, relatively new to Cohesity, SVP, Senior Vice President, General Manager of the cloud. Obviously, AWS, the biggest cloud, there's other clouds. What attracted you to Cohesity? What was the key thing that attracted you to this company to take a leadership role as this next wave comes in for cloud, and security and what Cohesity is doing? >> Yeah, there are a couple of reasons. Number one and most important was the maturity of the product and the quality of the product. Mohit Aron was our founder, you know, known as the grandfather or as the father of hyperconverge networking. >> He's a legend. >> He's a legend, right? >> (laughs) Just say it. >> And he's built a phenomenal set of technologies that really helps customers and that brings me to the second point, which is customers. We are a customer-obsessed company. And as I was talking to Mohit and Sanjay was our CEO, and Lynn was our CMO and others in the company, it was very evident to me that the core DNA of the company is really helping our customers be successful. Those two things put together. And the third thing, really, I am very culturally-obsessed when it comes to how organizations are run. We have a very strong culture in terms of how we treat employees, how we build the right set of products, and how we go to market. Right? Those three things put together, helped me really make a decision. Obviously, the leadership team within Cohesity was top notch as well. So every one of them that I spoke to had that same core belief system. That had helped a lot. >> Sanjay's a good friend of theCUBE, we've interviewed him many times with VMware. Paul, you know Sanjay's, he loves to get on cam. We hope to have him on tomorrow, if we can get him on the calendar. But you know, Sanjay told me one time, "I never missed a quarter." In his SAP, VMware, he's proud. We'll see, Paul, we're- >> Well, I'm going to hold him to that. >> We better not miss a quarter, I'm going to hold him to that. How's business? How's it, healthy? >> It's been great. We are seeing consistent demand for all of our products. As you can see, we continue to release new products into the market that customers are asking for. We are listening to what customers really want. Our roadmap is really based on two things, customer demand and market and where the market is growing. We have to stay on top of how the market is evolving based on the new challenges that customers are facing. Right? So markets, we are doing really good, company continues to grow and Sanjay has been fantastic in terms of driving that leadership. >> Yeah, he's a good driver. And again, he's Mr. Quarter for a reason, he's disciplined. >> (laughs) Very disciplined. >> Another reason, initiative, Cohesity's is the data security alliance. You put together a group of about a dozen security companies. Getting security companies to work with each other is always a challenge. How did you convince them to join with you? >> Well, one, we aligned on a mission. I mean, in the end, all the partners that we are talking about, they all care about what customers want. And we talked earlier about having that, you know, what is that single pane of glass when it comes to security? Is there one? Probably not. But if you can reduce the chatter, and the noise amongst all these companies, that helps. The other thing is they also understood our mission was really around the security, around data. We talked earlier about how security used to be very parameter or centric, but what you're really trying to save and secure is your data, which is your Queen Bee. And so a couple of months ago at our customer advisory council, I talked about moving and shifting the focus of security to be very data centric. And what we do in this partnership and alliance is a true integration. So there's a lot of engineering work that goes in, is us providing insights around the data to the security partners who can then leverage that to help customers be protected early on. Conversely, they can provide insights into an attack that's emanating possibly, to let us know that there's something happening, so we can lock up the data. So it's a bidirectional, symbiotic relationship between these partners and they all believe in that common cause of making sure the customers get protected. As we talked about earlier, lots of cyber attacks happening even as we speak, if we can collectively do something good in terms of making customers secure and successful, let's do it. >> So what will result from this alliance other than a press release? >> Customers will be successful, hopefully, not just protect customers from ransomware attacks, but also respond and recover if something does happen. We also announce our security council led by Kevin Mandia, and then we have some other big security advisors in that council as well. And that's been very helpful. So it's not just about the product itself, but it's also the collective experience of all these folks who can help and advise and coach CSOs, and other organizations on, what are the best practices? What are the things you're not really considering? What is the vision for you from an architecture standpoint? How is security threats starting to get more, and more mature? And how can you account for that? How can you reduce cost, to your point, right? How can you reduce cost when it comes to managing all these security solutions? >> No, there's no industry where working, it's more important for vendors to work together than in this one. >> Absolutely. I mean, especially for security, I don't think there's a one size fits all solution. So we have to work together. Right? >> What's your state of the union? You were at HashiCorp before you came here, you've been in the industry for a while, you've seen a few cycles of innovation. We're in a really weird time right now, because AWS wasn't really as powerful in 2008, when the last recession was hard too. They weren't really that big then. Now, they're a big part of the economic equation. So agility means fast speed. Can they help us get out of the pandemic? Customer's going to tighten their belts? Is there going to be a pullback? Is there tech spending? All these questions are looming. What are your customers seeing? What do you think is going to happen given the history? 'Cause I don't see the building stopping. I think you'll see more cloud, more savings. So is there fine-tuning solutions? What are customers thinking like now? >> I mean, if you think back to the last recession, the last major one, 2009, that's really about the time when you saw customers thinking about that whole digital transformation, because they started understanding that the way to connect with customers is through a digital engagement. Right? Now, as we've gone through a 10, 15 year period where there has been a lot of digital transformation, there's been a lot of investment in the cloud. Cloud is no longer seen with suspicion. Now, it's about getting smart on how to use it, how to build the right applications. Are there the right set of applications that need to stay in the cloud? And there might be others that need to stay on-prem. Right? I've talked to customers and CIOs who've mentioned to me in the past, that they would go a hundred percent in the cloud, and six months later they come back and they're like, "Nope, you're not going a hundred percent in the cloud. Maybe it's 10% or 15%." >> So they're moving. So what's your plan? You're the GM, you're in charge, you've got to take that next hill. Is it a tailwind, headwind? You've got to navigate the waters here, so to speak, mixed metaphors, but for the most part, you got a business opportunity. >> Absolutely. >> What's the outlook look like? What's your vision? What's the plan? >> Yeah. When it comes to cloud, there are certain things that are a common denominator. Right? One is how do you enable not just applications that are completely on cloud, but also that's on-prem? So for us, that hybrid movement is extremely important. But to create a single seamless UI and experience from an end-customer perspective. So for me, maintaining that and more at team, the R and D team at Cohesity have done a phenomenal job around that. For me, it's to maintain that, and then build additional workloads that make sense from a customer standpoint. There's a lot of investment customers are making. We also have to make sure that they're utilized correctly, and their stored, backed up data, recovered in a way that makes sense for them. And then if things do go south in terms of attacks or other issues, how can we help them get back up to speed, and make sure their business does not suffer? Right? So all of those combined, I think from a cloud perspective, it's the agility, the scalability, and the speed and swiftness that we can work with. >> Well, it sounds like he's ready for the Instagram Real Challenge, our new format on theCUBE. We're going to do a little segment where you can deliver a YouTube Short, Instagram Reel, TikTok or CUBE Gem. More of a thought leadership soundbite for 30 seconds around your view of why is cloud important right now. What's going on at this event that people should pay attention to? What's Cohesity doing? If you can put together a reel, a sizzle reel, or a thought leadership statement. What would that be? >> It would be that cloud is important for any business to be successful. And that's a given right now. I mean, digital transformation is an overused term, but the reality is it's here to stay. And it is the reason why everybody has a mobile phone. Half the people walking on the floor right now is looking at their phone and walking around. And that's your engagement method. So if you don't transform yourself to be able to connect with your end-user, your customer, you will not be successful. And Cohesity can help you by making sure that all of that data that you have, everything that you need in order to be successful to drive that engagement with your customers secure is backed up. No matter what, we will get you back up and running, and you will be successful. And we are in the success journey with you. >> Amith Nair, Senior Vice President, General Manager, Cohesity, the Cloud. Thanks for coming on theCUBE. For Paul Gillen, my co-host. I'm John Furrier here, live on the floor, wrapping up day two, few more segments, stay with us. We got a lot of action coming. We'll be right back with more after the short break. theCUBE, the leader in tech coverage. (bright music)

(upbeat intro music) >> Good afternoon, ladies and gentlemen and welcome back to fabulous Las Vegas, Nevada where we are theCUBE covering AWS re:Invent for the 10th year in a row. John Furrier, you've been here for all 10. How does this one stack up? >> It's feeling great. It's just back into the saddle of more people. Everyone's getting bigger and growing up. The companies that were originally on are getting stronger, bigger. They're doing takeovers in restaurants and still new players are coming in. More startups are coming in and taking care of what I call the (indistinct) on classic, all the primitives. And then you starting to see a lot more ecosystem platforms building on top of AWS. I call that NextGen Cloud, NextGen AWS. It's happening. It's happening right now. >> Best thing about all of these startups is they grow up, they mature, and we stay the same age, John. (John laughing) All right. All right. All right. Very excited to introduce you our next guest, he wears a lot of hats as the CEO, founder, and chairman at Reltio, please welcome Manish. Manish, welcome to the show. How is your show going so far? >> Well, thank you so much. You know, this is amazing. Just the energy, the number of people. You know, I was here last year, just after the pandemic, and I think it's almost double, if not more the number of people this year. >> John: Pushing 50,000. The high water mark was 65,000 in 2019. >> We should be doing like a Price Is Right sort of thing here on the show and figure out. >> Yeah, $1. >> Savannah: Yeah, yeah. (laughing) One guest, 80,000 guests. How many guests are here? Just in case the audience is not familiar, we know you're fast growing, very exciting business. Tell us what Reltio does. >> So, Reltio is a SaaS platform for data unification and we started Reltio in 2011. We have been serving some of the largest customers across industries like life sciences, healthcare, financial services, insurance, high tech, and retail. Those are, you know, some of the areas that we are focused on. The product capabilities are horizontal because we see the same data problem across every industry. Highly fragmented, highly siloed data that is slowing down the business for every organization out there. And that's the problem that we are solving. We are breaking down these silos, you know, one profile or one record, or one customer product supplier information record at a time, and bringing the acceleration of this unified data to every organization. >> This is the show Steam this year, Adam Celeste is going to be on stage talking about data end to end. Okay. Integrating in all aspects of a company. The word data analyst probably goes away pretty shortly. Everyone was going to be using data. This has been, and he talks about horizontal and vertical use cases. We've been saying that in theCUBE, I think it was about seven years ago, we first said we're going to start to see horizontally scalable data not just compute and cloud. This is now primetime conversation. Making that all work with governance is a real hard problem. Understanding the data. Companies have to put this horizontal and vertical capabilities in place together. >> Absolutely. You know, the data problem may be a horizontal problem, but every industry or vertical that you go into adds its own nuance or flavor to it. And that's why, you know, this has to be a combination of the horizontal and vertical. And we at Reltio thought about this for a while, where, you know, every time we enter a conversation, we are talking about patient data or physician data or client data and financial services or policy and customer information and insurance. But every time it's the number of silos that we encounter that is just an increasing number of applications, increasing number of third party data sources, and bringing that together in a manner where you can understand the semantics of it. Because, you know, every record is not created equal. Every piece of information is not created equal. But at the same time, you have to stitch it together in order to create that holistic, you know, the so-called 360 degree view. Because without that, the types of problems that you're trying to solve are not possible. Right? It's not possible to make those breakthroughs. And that's where I think the problem may be horizontal, but the application of the capabilities has to be verticalized. >> John: I'm smiling because, you know, when you're a founder like you are, and Dave, a lot here are at theCUBE, you're often misunderstood before people figure out what you do and why you started the company. And I can imagine, and knowing you and covering your company, that this is not just yesterday you came up with this idea that now everyone's talking about. There was probably moments in your history when you started, you're scratching it, "Hey the future's going to be this horizontal and vertical, especially where machine learning needs to know the data, the linguistics, whatever the data is, it's got to be very particular for the vertical, but you need to expand it." So when did you have the moment where people finally figured out like, what you guys doing is, like, relevant? I mean, now the whole world now sees- >> Savannah: Overnight success 11 years later. >> John: This shows the first time I've heard Amazon and the industry generally agree that horizontally scalable data systems with vertical value, that it's natural. We've been saying it for seven years on theCUBE. You've been doing the startup. >> Yeah. >> As a founder, you were there early. Now people are getting it. What's it like? Tell, take us through. When did you have the moment? When did you tipping point for the world getting it? >> Yeah, and you know, the key thing to remember is that, you know, not only have I been in this space for a long time but the experiences that we have gone through starting in 2011, there was a lot of focus on, you know, even AWS was at that point in time in the infancy stages. >> Yeah. >> And we said that we are going to set up a software as a service capability that runs only on public cloud because we had seen what customers had tried to do behind their firewalls and the types of hurdles that they had run into before. And while the concept was still in its nascent stages, but the directional signals, the fact that number of applications that you see in use today across any organization, that's growing. It used to be a case when in early 2000s, you know, this is early part of my career, where having six different applications across the enterprise landscape was considered complex. But now those same organizations are talking about 400, 500, a thousand different applications that they're using to run their business end to end. So, you know, this direction was clear. The need for digital transformation was becoming clear. And the fact that, you know, cloud was the only vehicle that you could use to solve these types of ad scale problems was also becoming clear. But what wasn't yet mainstream was this notion that, you know, if you're doing digital transformation, you need access to clean, consistent, trusted information. Or if you're doing machine learning or any kind of data analytics, you need similar kinds of trusted information. It wasn't a mainstream concept, but people were struggling with it because, you know, the whole notion of garbage in garbage out was becoming clearer to them as they started running into hurdles. And it's great to see that now, you know, after having gone through the transformation of, yes, we have provided the compute and the storage, but now we really need to unlock the value out of data that goes on this compute and storage. You know, it's great to see that even Amazon or AWS is talking about it. >> Well, as a founder, it's satisfying, and congratulations, we've been covering that. I got to ask, you mention this end to end. I like the example of in the 2006 applications considered complex, now hundreds and thousands of workloads are on an enterprise. Today we're going to hear more end to end data services on AWS and off AWS, hybrid or edge or whatever, that's happens. Now cross, it sounds like it's going to get more complex still. >> I mean... >> John: Right. I mean, that's not easy. >> Savannah: The gentle understatement of the century. I love that. Yes. >> If Adam's message is end to end, it's going to be more complex. How does it get easier? Because the enterprise, you know, the enterprise vendors love solving complexity with more complexity. That's the wrong answer. >> Well, you're absolutely right that things are going to get more complex. But you know, this is where, whether it is Amazon or you know, us, Reltio as a vendor coming in, the goal should always be what are we going to simplify for the customer? Because they are going to end up with a complex landscape on their hands anyway. Right? >> Savannah: Right. >> So that is where, what can be below the surface and simplified for the customers to use versus bringing their focus to the business value that they can get out of it. Unlocking that business value has to be the key aspect that we have to bring to the front. And, you know, that is where, yes, the landscape complexity may grow, but how is the solution making it simpler, easier, faster for you to get value out of the data that you're trying to work with? >> As a mission, that seems very clear and clean cut, but I'm curious, I can imagine there's so many different things that you're prioritizing when you're thinking about how to solve those problems. What is that decision matrix like for you? >> For us, it goes back to the core focus and the core problem that we are in the business of solving which is in a siloed, fragmented landscape, how can we create a single source of truth orientation that your business can depend on? If you're looking for the unified view of the customer, the product, the supplier, the location, the asset, all these are elements that are critical or crucial for you to run your business end to end. And we are there to provide that solution as Reltio to our customers. So, you know, we always, for our decision matrix have to go back to are we simplifying that problem for our customers and how much faster, easier, nimbler can it be, you know, both as a solution and also the time to value that it brings to the equation for the customer. >> Super important, end of the equation. Clearly you are on to something. You are not only a unicorn company, unicorn company being evaluated at over $1 billion latest evaluation, correct me if I'm wrong, is $1.7 billion as of last year. But you are also a centaur, which is seven times more rare than a unicorn, which for the audience maybe not familiar with the mythical creatures that define the Silicon Valley nomenclature in Lexicon. A centaur is a company with a hundred million in annual reoccurring revenue. How does it feel to be able to say that as a CEO or to hear me say that to you? >> Well, as a CEO, it's, you know, something that we have been working towards. the goal that we can deliver value to our customers, help every industry, you know, you just think about the types of products that you touch in a day, whether it's, you know, any healthcare related products that you're looking at. We are working with customers who are solving for the patient record to be unified with our platform. We are working with financial services companies who are helping you simplify how you do banking with them. We are working with retailers who are working in the area of, you know, leisure apparel or athletic goods and they are using our capabilities to simplify how they deliver better experience to you. So as I go across these industries, being able to influence and touch and simplify things overall for the customers that these companies are serving, that's an amazing feeling. And, you know, doing this while we are also making sure that we can build a durable business that has substantial revenue behind it- >> Savannah: Substantial. >> Gives us a lot of legs to stand on and talk about how we can change how the companies should run their entire data stack. >> And you're obviously a very efficient team practicing what you teach. You told me how many employees that you have? >> We have 450 employees across the globe. >> 450 employees and a hundred million in reoccurring revenue. It's pretty strong. It's pretty strong. >> Thank you. >> That's a quarter million in rev per employee. They're doing a pretty good job. That's absolutely fantastic. >> The cloud has been very successful, partnering with the cloud, a lot of leverage for the cloud. >> And that's been a part of our thesis from the very beginning that, you know, the capabilities that we build and bring to life have to be built on public cloud infrastructure. That's something that has been core to our innovation cycle because we look at it as a layer cake of innovation that we sit on and we can continue to drive faster value for our customers. >> John: Okay, so normally we do a bumper sticker. Tell me the bumper sticker for the show. We changed it to kind of modernize it called the Insta Challenge, Instagram challenge. Instagram has reels, short videos. What's the Instagram reel from your perspective? You have to do an Instagram reel right now about why this time in history, this time in for Amazon web services, this point for Reltio. Why is this moment in time important in the computer industry? Because, you know, we've reported, I put a story out, NextGen Clouds here. People are seeing their status go from ISV to ecosystem platforms on top of AWS. Your success has continued to grow. Something's going on. What's the Instagram reel about why this year's so important in the history of the cloud? >> Well, you know, just think about the overall macroeconomic conditions. You know, everybody's trying to think about where the next, you know, the set of growth is going to come from or how we are going to tackle, you know, what we have as challenges in front of us. And at the end of the day, most of the efficiency that came from applying new applications or, you know, buying new products in the application space has delivered its value. The next unlock is going to come from data. And that is the key that we have to think about because the traditional model of going across 500 different applications to run your business is no longer going to be a scalable model to work with. If you really want to move faster with your business, you have to think about how to use data as a strategic asset and think about things differently. And we are talking about delivering experience at the edge, delivering, you know, real time type of engagement with the customers that we work with. And that is where the entire data value proposition starts to deliver a whole new set of options to the customers. And that's something that we all have to think about differently. It's going to require a fundamentally different architecture, innovation, leading with data instead of thinking about the traditional landscape that we have been running with. >> Leading with data and transforming architecture. A couple themes we've had on the show lately already. >> John: Well I think there's been a great, I mean this is a great leadership example of what's going on in the industry. As young people are looking at their careers. I've talked with a lot of folks under 30, they're trying to figure out what's a good career path and they're looking at all this change in front of them. >> That's a great point, John. >> Whether it's a computer science student or someone in healthcare, these industries are being reinvented with data. What's your advice to those young, this up and coming generation that might not take the traditional path traveled 'cause it might not be there. What's your advice for those people making these career decisions? >> I think there are two things that are relevant to every career option out there. Knowledge and awareness of data and how to apply computing techniques to the data is key and relevant. It's the language that we all have to learn and be familiar with. Without that, you know, you'll be missing a key part of your arsenal that you will be required to bring to work but won't have access to if you're not well-versed or familiar with those two areas. So this is lingua franca that we all have to get used to. >> Data and computer technology applied to business or some application or some problem. >> Manish: Applied to business. You know, figuring out how to apply it to deliver business outcomes is the key thing to keep in mind. >> Okay. >> Yeah. Last question for you to wrap us up. It's obviously an exciting, thrilling, vibrant moment here on the show floor, but I'm curious because I can imagine some of your customers, especially given the scale that they're at, I mean we're talking about some Fortune 100s here, how are you delivering value in this uncertain market? I mean, I know you solved this baseline problem but I can imagine there's a little bit of frantic energy within your customer base. >> Manish: Yeah. You know, with data this has been a traditional challenge. Everybody talks about the motherhood and apple pie. If you have better data, you can drive better outcomes. But some of the work that we have been doing is quantifying, measuring those outcomes and translating what the dollar impact of that value is for each one of the customers. And this is where the work that we have done with large, you know, let's say life sciences companies like AstraZeneca or GSK or in financial services with companies like Northwestern Mutual or Fidelity or, you know, common household names like McDonald's where they're delivering their digital transformation with the data capabilities that we are helping build with them. That's the key part that's been, you know, extremely valuable. And that is where in each one of these situations, we are helping them measure what the ROI is at every turn. So being able to go into these discussions with the hard dollar ROI that you can expect out of it is the key thing that we are focused on. >> And that's so mission critical now and at any economic juncture. Just to echo that, I noticed that Forrester did an independent study looking at customers that invested in your MDM solution. 366% ROI and a total net present value of 13 million over three years. So you clearly deliver on what you just promised there with customers and brands that we touch in all of our everyday lives. Manish, thank you so much for being on the show with us today. You and Reltio are clearly crushing it. We can't wait to have you back hopefully for some more exciting updates at next year's AWS re:Invent. John, thanks for- >> Or sooner. >> Yeah, yeah. Or sooner or maybe in the studios or who knows, at one of the other fabulous events we'll all be at. I'm sure you'll be traveling around given the success that the company is seeing. And John, thanks for bringing the young folks into the conversation, was a really nice touch. >> We got skill gaps, we might as well solve that right now. >> Yeah. And I like to think that there are young minds watching theCUBE or at least watching, maybe their parents are- >> We're streaming to Twitch. All the gamers are watching this right now. Stop playing the video games. >> We have the hottest stream on Twitch right now if you're not already ready for it. John Furrier, Manish Sood, thank you so much for being on the show with us. Thank all of you at home or at the office or in outer space or wherever you happen to be tuned in to this fabulous live stream. You are watching theCUBE, the leader in high tech coverage. My name is Savannah Peterson. We're at AWS re:Invent here in Las Vegas where we'll have our head in the clouds all week.

>>Good evening everyone and welcome back to Sparkly Sin City, Las Vegas, Nevada, where we are here with the cube covering AWS Reinvent for the 10th year in a row. John Furrier has been here for all 10. John, we are in our last session of day one. How does it compare? >>I just graduated high school 10 years ago. It's exciting to be, here's been a long time. We've gotten a lot older. My >>Got your brain is complex. You've been a lot in there. So fast. >>Graduated eight in high school. You know how it's No. All good. This is what's going on. This next segment, wrapping up day one, which is like the the kickoff. The Mondays great year. I mean Tuesdays coming tomorrow big days. The announcements are all around the kind of next gen and you're starting to see partnering and integration is a huge part of this next wave cuz API's at the cloud, next gen cloud's gonna be deep engineering integration and you're gonna start to see business relationships and business transformation scale a horizontally, not only across applications but companies. This has been going on for a while, covering it. This next segment is gonna be one of those things that we're gonna look at as something that's gonna happen more and more on >>Yeah, I think so. It's what we've been talking about all day. Without further ado, I would like to welcome our very exciting guest for this final segment, trust from single store. Thank you for being here. And we also have him on from IBM Data and ai. Y'all are partners. Been partners for about a year. I'm gonna go out on a limb only because their legacy and suspect that a few people, a few more people might know what IBM does versus what a single store does. So why don't you just give us a little bit of background so everybody knows what's going on. >>Yeah, so single store is a relational database. It's a foundational relational systems, but the thing that we do the best is what we call us realtime analytics. So we have these systems that are legacy, which which do operations or analytics. And if you wanted to bring them together, like most of the applications want to, it's really a big hassle. You have to build an ETL pipeline, you'd have to duplicate the data. It's really faulty systems all over the place and you won't get the insights really quickly. Single store is trying to solve that problem elegantly by having an architecture that brings both operational and analytics in one place. >>Brilliant. >>You guys had a big funding now expanding men. Sequel, single store databases, 46 billion again, databases. We've been saying this in the queue for 12 years have been great and recently not one database will rule the world. We know that. That's, everyone knows that databases, data code, cloud scale, this is the convergence now of all that coming together where data, this reinvent is the theme. Everyone will be talking about end to end data, new kinds of specialized services, faster performance, new kinds of application development. This is the big part of why you guys are working together. Explain the relationship, how you guys are partnering and engineering together. >>Yeah, absolutely. I think so ibm, right? I think we are mainly into hybrid cloud and ai and one of the things we are looking at is expanding our ecosystem, right? Because we have gaps and as opposed to building everything organically, we want to partner with the likes of single store, which have unique capabilities that complement what we have. Because at the end of the day, customers are looking for an end to end solution that's also business problems. And they are very good at real time data analytics and hit staff, right? Because we have transactional databases, analytical databases, data lakes, but head staff is a gap that we currently have. And by partnering with them we can essentially address the needs of our customers and also what we plan to do is try to integrate our products and solutions with that so that when we can deliver a solution to our customers, >>This is why I was saying earlier, I think this is a a tell sign of what's coming from a lot of use cases where people are partnering right now you got the clouds, a bunch of building blocks. If you put it together yourself, you can build a durable system, very stable if you want out of the box solution, you can get that pre-built, but you really can't optimize. It breaks, you gotta replace it. High level engineering systems together is a little bit different, not just buying something out of the box. You guys are working together. This is kind of an end to end dynamic that we're gonna hear a lot more about at reinvent from the CEO ofs. But you guys are doing it across companies, not just with aws. Can you guys share this new engineering business model use case? Do you agree with what I'm saying? Do you think that's No, exactly. Do you think John's crazy, crazy? I mean I all discourse, you got out of the box, engineer it yourself, but then now you're, when people do joint engineering project, right? They're different. Yeah, >>Yeah. No, I mean, you know, I think our partnership is a, is a testament to what you just said, right? When you think about how to achieve realtime insights, the data comes into the system and, and the customers and new applications want insights as soon as the data comes into the system. So what we have done is basically build an architecture that enables that we have our own storage and query engine indexing, et cetera. And so we've innovated in our indexing in our database engine, but we wanna go further than that. We wanna be able to exploit the innovation that's happening at ibm. A very good example is, for instance, we have a native connector with Cognos, their BI dashboards right? To reason data very natively. So we build a hyper efficient system that moves the data very efficiently. A very other good example is embedded ai. >>So IBM of course has built AI chip and they have basically advanced quite a bit into the embedded ai, custom ai. So what we have done is, is as a true marriage between the engineering teams here, we make sure that the data in single store can natively exploit that kind of goodness. So we have taken their libraries. So if you have have data in single store, like let's imagine if you have Twitter data, if you wanna do sentiment analysis, you don't have to move the data out model, drain the model outside, et cetera. We just have the pre-built embedded AI libraries already. So it's a, it's a pure engineering manage there that kind of opens up a lot more insights than just simple analytics and >>Cost by the way too. Moving data around >>Another big theme. Yeah. >>And latency and speed is everything about single store and you know, it couldn't have happened without this kind of a partnership. >>So you've been at IBM for almost two decades, don't look it, but at nearly 17 years in how has, and maybe it hasn't, so feel free to educate us. How has, how has IBM's approach to AI and ML evolved as well as looking to involve partnerships in the ecosystem as a, as a collaborative raise the water level together force? >>Yeah, absolutely. So I think when we initially started ai, right? I think we are, if you recollect Watson was the forefront of ai. We started the whole journey. I think our focus was more on end solutions, both horizontal and vertical. Watson Health, which is more vertically focused. We were also looking at Watson Assistant and Watson Discovery, which were more horizontally focused. I think it it, that whole strategy of the world period of time. Now we are trying to be more open. For example, this whole embedable AI that CICE was talking about. Yeah, it's essentially making the guts of our AI libraries, making them available for partners and ISVs to build their own applications and solutions. We've been using it historically within our own products the past few years, but now we are making it available. So that, how >>Big of a shift is that? Do, do you think we're seeing a more open and collaborative ecosystem in the space in general? >>Absolutely. Because I mean if you think about it, in my opinion, everybody is moving towards AI and that's the future. And you have two option. Either you build it on your own, which is gonna require significant amount of time, effort, investment, research, or you partner with the likes of ibm, which has been doing it for a while, right? And it has the ability to scale to the requirements of all the enterprises and partners. So you have that option and some companies are picking to do it on their own, but I believe that there's a huge amount of opportunity where people are looking to partner and source what's already available as opposed to investing from the scratch >>Classic buy versus build analysis for them to figure out, yeah, to get into the game >>And, and, and why reinvent the wheel when we're all trying to do things at, at not just scale but orders of magnitude faster and and more efficiently than we were before. It, it makes sense to share, but it's, it is, it does feel like a bit of a shift almost paradigm shift in, in the culture of competition versus how we're gonna creatively solve these problems. There's room for a lot of players here, I think. And yeah, it's, I don't >>Know, it's really, I wanted to ask if you don't mind me jumping in on that. So, okay, I get that people buy a bill I'm gonna use existing or build my own. The decision point on that is, to your point about the path of getting the path of AI is do I have the core competency skills, gap's a big issue. So, okay, the cube, if you had ai, we'd take it cuz we don't have any AI engineers around yet to build out on all the linguistic data we have. So we might use your ai but I might say this to then and we want to have a core competency. How do companies get that core competency going while using and partnering with, with ai? What you guys, what do you guys see as a way for them to get going? Because I think some people probably want to have core competency of >>Ai. Yeah, so I think, again, I think I, I wanna distinguish between a solution which requires core competency. You need expertise on the use case and you need expertise on your industry vertical and your customers versus the foundational components of ai, which are like, which are agnostic to the core competency, right? Because you take the foundational piece and then you further train it and define it for your specific use case. So we are not saying that we are experts in all the industry verticals. What we are good at is like foundational components, which is what we wanna provide. Got it. >>Yeah, that's the hard deep yes. Heavy lift. >>Yeah. And I can, I can give a color to that question from our perspective, right? When we think about what is our core competency, it's about databases, right? But there's a, some biotic relationship between data and ai, you know, they sort of like really move each other, right? You >>Need, they kind of can't have one without the other. You can, >>Right? And so the, the question is how do we make sure that we expand that, that that relationship where our customers can operationalize their AI applications closer to the data, not move the data somewhere else and do the modeling and then training somewhere else and dealing with multiple systems, et cetera. And this is where this kind of a cross engineering relationship helps. >>Awesome. Awesome. Great. And then I think companies are gonna want to have that baseline foundation and then start hiring in learning. It's like driving the car. You get the keys when you're ready to go. >>Yeah, >>Yeah. Think I'll give you a simple example, right? >>I want that turnkey lifestyle. We all do. Yeah, >>Yeah. Let me, let me just give you a quick analogy, right? For example, you can, you can basically make the engines and the car on your own or you can source the engine and you can make the car. So it's, it's basically an option that you can decide. The same thing with airplanes as well, right? Whether you wanna make the whole thing or whether you wanna source from someone who is already good at doing that piece, right? So that's, >>Or even create a new alloy for that matter. I mean you can take it all the way down in that analogy, >>Right? Is there a structural change and how companies are laying out their architecture in this modern era as we start to see this next let gen cloud emerge, teams, security teams becoming much more focused data teams. Its building into the DevOps into the developer pipeline, seeing that trend. What do you guys see in the modern data stack kind of evolution? Is there a data solutions architect coming? Do they exist yet? Is that what we're gonna see? Is it data as code automation? How do you guys see this landscape of the evolving persona? >>I mean if you look at the modern data stack as it is defined today, it is too detailed, it's too OSes and there are way too many layers, right? There are at least five different layers. You gotta have like a storage you replicate to do real time insights and then there's a query layer, visualization and then ai, right? So you have too many ETL pipelines in between, too many services, too many choke points, too many failures, >>Right? Etl, that's the dirty three letter word. >>Say no to ETL >>Adam Celeste, that's his quote, not mine. We hear that. >>Yeah. I mean there are different names to it. They don't call it etl, we call it replication, whatnot. But the point is hassle >>Data is getting more hassle. More >>Hassle. Yeah. The data is ultimately getting replicated in the modern data stack, right? And that's kind of one of our thesis at single store, which is that you'd have to converge not hyper specialize and conversation and convergence is possible in certain areas, right? When you think about operational analytics as two different aspects of the data pipeline, it is possible to bring them together. And we have done it, we have a lot of proof points to it, our customer stories speak to it and that is one area of convergence. We need to see more of it. The relationship with IBM is sort of another step of convergence wherein the, the final phases, the operation analytics is coming together and can we take analytics visualization with reports and dashboards and AI together. This is where Cognos and embedded AI comes into together, right? So we believe in single store, which is really conversions >>One single path. >>A shocking, a shocking tie >>Back there. So, so obviously, you know one of the things we love to joke about in the cube cuz we like to goof on the old enterprise is they solve complexity by adding more complexity. That's old. Old thinking. The new thinking is put it under the covers, abstract the way the complexities and make it easier. That's right. So how do you guys see that? Because this end to end story is not getting less complicated. It's actually, I believe increasing and complication complexity. However there's opportunities doing >>It >>More faster to put it under the covers or put it under the hood. What do you guys think about the how, how this new complexity gets managed or in this new data world we're gonna be coming in? >>Yeah, so I think you're absolutely right. It's the world is becoming more complex, technology is becoming more complex and I think there is a real need and it's not just from coming from us, it's also coming from the customers to simplify things. So our approach around AI is exactly that because we are essentially providing libraries, just like you have Python libraries, there are libraries now you have AI libraries that you can go infuse and embed deeply within applications and solutions. So it becomes integrated and simplistic for the customer point of view. From a user point of view, it's, it's very simple to consume, right? So that's what we are doing and I think single store is doing that with data, simplifying data and we are trying to do that with the rest of the portfolio, specifically ai. >>It's no wonder there's a lot of synergy between the two companies. John, do you think they're ready for the Instagram >>Challenge? Yes, they're ready. Uhoh >>Think they're ready. So we're doing a bit of a challenge. A little 32nd off the cuff. What's the most important takeaway? This could be your, think of it as your thought leadership sound bite from AWS >>2023 on Instagram reel. I'm scrolling. That's the Instagram, it's >>Your moment to stand out. Yeah, exactly. Stress. You look like you're ready to rock. Let's go for it. You've got that smile, I'm gonna let you go. Oh >>Goodness. You know, there is, there's this quote from astrophysics, space moves matter, a matter tells space how to curve. They have that kind of a relationship. I see the same between AI and data, right? They need to move together. And so AI is possible only with right data and, and data is meaningless without good insights through ai. They really have that kind of relationship and you would see a lot more of that happening in the future. The future of data and AI are combined and that's gonna happen. Accelerate a lot faster. >>Sures, well done. Wow. Thank you. I am very impressed. It's tough hacks to follow. You ready for it though? Let's go. Absolutely. >>Yeah. So just, just to add what is said, right, I think there's a quote from Rob Thomas, one of our leaders at ibm. There's no AI without ia. Essentially there's no AI without information architecture, which essentially data. But I wanna add one more thing. There's a lot of buzz around ai. I mean we are talking about simplicity here. AI in my opinion is three things and three things only. Either you use AI to predict future for forecasting, use AI to automate things. It could be simple, mundane task, it would be complex tasks depending on how exactly you want to use it. And third is to optimize. So predict, automate, optimize. Anything else is buzz. >>Okay. >>Brilliantly said. Honestly, I think you both probably hit the 32nd time mark that we gave you there. And the enthusiasm loved your hunger on that. You were born ready for that kind of pitch. I think they both nailed it for the, >>They nailed it. Nailed it. Well done. >>I I think that about sums it up for us. One last closing note and opportunity for you. You have a V 8.0 product coming out soon, December 13th if I'm not mistaken. You wanna give us a quick 15 second preview of that? >>Super excited about this. This is one of the, one of our major releases. So we are evolving the system on multiple dimensions on enterprise and governance and programmability. So there are certain features that some of our customers are aware of. We have made huge performance gains in our JSON access. We made it easy for people to consume, blossom on OnPrem and hybrid architectures. There are multiple other things that we're gonna put out on, on our site. So it's coming out on December 13th. It's, it's a major next phase of our >>System. And real quick, wasm is the web assembly moment. Correct. And the new >>About, we have pioneers in that we, we be wasm inside the engine. So you could run complex modules that are written in, could be C, could be rushed, could be Python. Instead of writing the the sequel and SQL as a store procedure, you could now run those modules inside. I >>Wanted to get that out there because at coupon we covered that >>Savannah Bay hot topic. Like, >>Like a blanket. We covered it like a blanket. >>Wow. >>On that glowing note, Dre, thank you so much for being here with us on the show. We hope to have both single store and IBM back on plenty more times in the future. Thank all of you for tuning in to our coverage here from Las Vegas in Nevada at AWS Reinvent 2022 with John Furrier. My name is Savannah Peterson. You're watching the Cube, the leader in high tech coverage. We'll see you tomorrow.