>> Announcer: Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel along with its eco-system partners. >> Hey, welcome back to theCUBE's coverage of AWS re:Invent '19. This is our third day in Vegas. That's a lot of Vegas. I am joined by my co-host Justin Warren, the founder and chief analyst at PivotNine, and Justin and I are welcoming back one of our CUBE alum. Joining us next from MongoDB is Sahir Azam, its chief product officer. Welcome back! >> Thank you so much, I'm happy to be here. >> So talk to us about what's going on at MongoDB, I know we've had you on the program before, we've had MongoDB, but what's sort of the latest and greatest? >> Yeah, so we're continuing to grow very fast, and especially our cloud product Atlas. We've got two million developers using the platform today, 13,000 customers, many of which are on the amazing AWS platform, and I think people are really embracing the idea of a multicloud database service and a data platform they can have the flexibility to work with no matter where they are. >> Talk about, sorry, Justin, about multicloud a little bit more because it is a symptom as one of our CEOs, Dave Vellante, calls it. A lot of companies have inherited it, it's more by whether it's organically, or it's by acquisition, or developer preference. It's a state in which a lot of businesses are operating, but it's challenging. >> Yes. >> What are some of the things that you're hearing with respect to customers? How can you help them deal better in that world? >> Sure. So, yeah we definitely see some of those exact trends, so, you know for large enterprises, many times, they have different use cases in different business units, where developers or application owners prefer different cloud providers. Oftentimes it's acquisition, but also at a strategic level, at the CTO, CIO, or even CEO level, you know, there is a forethought strategy that it's going to be a multicloud platform world, and now what we see is many customers are still very much focused on a single cloud provider to build-up the skills on, but with a close eye to a second or third tier provider in the architecture that they will scale and balance over time. So, I think it's early days, but the trend is definitely rising in what we're seeing. Now, one of the things that makes a multicloud strategy really hard to implement is the data. You know, especially transactional data that runs live applications that are serving real customers, that makes an application and a development team really stuck on a certain platform. So, what we're focused on at MongoDB is really de-coupling that data layer from the underlying cloud infrastructure providers such that if you want to leverage the benefits of the different services AWS has in their rich ecosystem, but then maybe plumb in something from another provider, we make that extremely easy to do with the click of a button, and move your data across those cloud providers. >> Yeah, so talk about the mechanism for doing that a little bit more, because that's really tricky to do, and that's one thing I think people have been concerned about the idea of multicloud, is that, well, are you actually running in multiple clouds simultaneously, or is it more that, well actually sometimes we just want to move a bit from here to there that we'll use for different applications? >> There's sort of three trends that we see you know, and we're a data platform player, so our use cases are sort of bounded around database technology, data analytics. So, the first is for customers who want high availability across multiple regions within a certain geography, so let's say you're dealing with personal information of German citizens in Germany, Amazon has a region in Germany, only one, and maybe you want Azure or GCP to be a second region for high availability, and you need to rely on a secondary provider, because there's only one from a particular cloud of choice in that geo, so that's sort of one high availability kind of use case. The second is leveraging the benefits of all these different services that the cloud providers themselves are releasing, so we hear a lot of customers that say, you know, Amazon's my preferred partner for operationalizing my app. We use their services, our database runs there, however, we may want to take some of that data, even if it's for a week, even for a few days, a month, and perhaps move it over to another provider to leverage some new analytic service or machine learning, or AI algorithm that they might have. Today, that's really challenging to do. It's the idea that you can click a button, and create that replica, and move that data over very easily is something that people are asking from us. And then the third is geographic reach. So, our database platform, Atlas runs in 70 global regions worldwide, across AWS, Azure, and GCP which makes it the most widely available databases service on the planet. And one of the interesting use cases for that is, let's say somebody is using a single cloud provider for 99% of their work load, but suddenly they see their app take off in Taiwan, you know, maybe another cloud provider has a region in Taiwan, just mix and match and add that region into the architecture very seamlessly. So, those kind of three categories, high availability within geos, the ability to leverage, you know, the rich service offerings and mix and match, and then the geographic reach, are the three things we see for multi plat at a strategic level, beyond the reactive angle of acquiring a company and learning how to have to manage multiple clouds that way. >> That does sound like it's a bit of a trend that we're hearing and particularly today, I think, Lisa, where enterprises want choice, and that customer choice, of being able to choose things that actually suit me, rather than necessarily which vendor I'm buying my infrastructure from. That sounds like something that we're hearing a lot. >> Yeah, and we've invested a lot of time, engineering effort, working with Amazon, working with Google, working with Microsoft, to unify that data layer across the three cloud providers, and I think that's something unique that Mongo's really focused on. >> But there were so many announcements that came out, in Andy Jassy's keynote a couple of days ago. I think I read 23 announcements just in the first 20 minutes, or something of his keynote. So much information, but I'm curious, did anything that they announced surprise you in terms of, hey, customers are living in this multicloud world, there's use cases, there's reasons for it? Any shift that Amazon is making or announced this week that you thought, yes, some of these things are becoming a reality? We have to go where the data is, and we have to deliver what's best for our customers. >> I mean, I think Amazon is a very customer-centric company. I don't think I heard any announcement that particularly acknowledged the fact that it's going to be a multicloud world, you know, I think they're still the market share leader, they have a rich set of offerings, and they're going to continue building on that which I think makes a lot of sense from the position that they're in. I think some of the announcements that are interesting to us, definitely the idea of having lower cost, higher performance ARM hardware and chips for our database vendor. If we can lower the price performance curve for customers on top of that infrastructure, that's exciting for us, and we always think it's interesting, in a AWS keynote that's two or three hours long that about a third or half of it is talk about data. We love data, so the more rich sets of services we can surround and integrate Mongo into, the better, so, exciting for us. >> Data seems to be like the next generation of cloud, data can become a huge asset for any business in any industry, whereas, there are companies and times where data was a risk, a vunerability. What is a great example, in your opinion, of a MongoDB customer who has done a great job of transforming to where data is now a huge asset, and a driver of business differentiation? >> So, one interesting customer example I really like is Axiom. They're a marketing data provider, data has been the heart of their business for a long time, but traditionally their business would be packaging up and shipping data sets to their end customers, in a very custom bespoke manner. What we worked with them on is leveraging our cloud platform Atlas, along with some API technologies that we have, and a product called Stitch, to make it very easy for them to create custom APIs to allow their end customers to access that data programmatically. And since we manage and run that on their behalf, their development team, their operations team don't have to worry about the plumbing and managing of all these API layers and all that, they just stamp out these custom APIs, we auto-scale them on top of the rich Mongo database on the back end, and so we've allowed them to really take the data business they were in, but really modernize it by exposing it directly to developers programmatically instead of just shipping data around which is expensive and cumbersome. So I think that's a really interesting example of a data company transforming itself, and kind of innovating in the cloud with some of the technologies we provide, obviously, on top of the Amazon platform. >> So, you mentioned transforming, that's definitely been a theme of the show. So MongoDB is a different way of actually managing data, so compared to traditional methods. A lot of enterprises still have a lot of investment in RDBMSs, more traditional kind of databases. What are you seeing when customers come to MongoDB and start using this different way of storing and managing data? What is that transition for them like? >> Sure, so I think the thing that MongoDB's inception 11 years ago through now, what drives our adoption, I should say, is really the fact that developers love our platform. The document model, the MongoDB API is just a much more flexible and natural way for developers to think about writing applications, so, you know, you're building an application, you might be managing a customer object, a product, an account. These are all sort of business objects that get represented in a developer's mind and then in an application, but then if you put that in a relational database, you're chopping that up into rows and tables, and then having to rejoin that back together just to make sense of the underlying information you're trying to represent. Mongo gets rid of all of that cognitive dissonance, and that's what really unlocks that developer productivity. Now, the interesting thing about MongoDB is as a non-relational database, we have looked at the legacy RDBMS providers and said, what are the things that are really strong about those platforms that we can bring forth and apply to this much more agile and natural data model? So things like data governance and schema, strong transactional guarantees, enterprise management functionality, enterprise security and encryption at a very deep level. These are things that large mission critical application developers and operators really need. And they don't typically find them in fast databases, scalable databases, like MongoDB. So what we've done is really merge the best of the legacy traditional databases, the things people expect in a rock-solid mission critical database, but brought it forward in a model that's much faster for developers to move quickly on, and so the way that represents itself in our business, roughly about a third of our business any given quarter, tends to come from legacy migrations off of some traditional relational database, and the driver for that is modernization. People want to move those apps to the cloud, they don't just want to lift and shift from one relational database to another necessarily, that might have certain cost benefits from one provider to another, but it doesn't unlock that developer agility, and that's why they're choosing MongoDB. >> So all in the spirit of transformation, the ability for MongoDB to unlock the developer productivity, one of the things Andy Jassy talked about on Tuesday was, one of the four essential pillars of transformation. It's got to come from the top down, it's got to come from that senior executive level, they've got to drive it down aggressively. As chief product officer, where are your conversations? Are you still, in terms of feedback and, you know, customer advisory information, are you still talking mostly to the developer folks who were the primary users, or are you also having those higher level-- >> Sahir: Both. >> Both, tell us a little bit about that. >> Now what's interesting about a data technology like Mongo is, it's not a top down sort of sell. No CIO, CTO, line-of-business executive is going to dictate down to their developers, thou shalt use this particular database technology, or what not. Every development team is going to choose a technology that allows them to move fast and meets their requirements. So, what we've really done is we've focused on engaging with our customers, our sales organization, our marketing organization, our developer relations organization, is merging a strategic top-down sort of model with those CIOs and business leaders about how MongoDB can transform their business as a data platform. Get that sponsorship, get that executive alignment, to be a strategic provider, but then at the same time, really fostering that community that MongoDB's always been known for bottoms up to make sure that more and more of these applications see the power and value of MongoDB. So we have to merge both those motions. If we were just bottoms up, then I think we wouldn't be as strategic as we are in many of these organizations in terms of how transformative as a vendor and a technology provider and partner we are. But at the same time, if we lost our roots with the developers, databases don't get chosen from the top down, they get introduced and put on the list, maybe, and sponsored into the account, but we've got to build and earn that trust with developers directly. >> Yeah, so you've had incredible success, incredible growth so far. >> Sahir: Thank you. >> What's next for Mongo? >> So, I think a big part of our journey for the last three or four years has been really, adding a second major growth engine to the company by building out our cloud business. So that was our MongoDB Atlas platform built on top of AWS, Azure, and GCP, and that is the fastest growing part of our business, and will clearly be, you know, the majority of our business in the future. The next year to two years, is really about transitioning from a single data product company to a data platform company. So earlier this year, we announced not just the core foundational database features we're always building on top of, but also a big step into analytics, with our Atlas Data Lake product, which allows development teams and analysts to run queries using the Mongo query language they love, but on top of S3, where they have mountains and mountains of data stored from all these different sources. And at the same time we've also added things like full text indexing, so instead of standing up a, search cluster next to your Mongo database, having to worry about copying data just to get full text search in your application, we merge that capability directly into the Atlas platform. So, a big part of our journey is saying, once we have so many customers on the platform, how can we add more value, and yet still merge that all in a very expressive developer experience with our query language? So they're not dealing with 13 different databases and four copies of their data and integrating and shuttling that all around, but is a very prescriptive experience for them. >> Wow, Sahir, thank you for sharing all the innovations that are going on at MongoDB with Justin and me on the program today. A lot going on. >> Yeah, thank you for having me. I really enjoyed the show and coming on theCUBE. >> Lisa: Good, we appreciate your time. >> Great. >> For my co-host Justin Warren, I'm Lisa Martin, and you've been watching theCUBE from Vegas, baby. AWS re:Invent '19. Thanks for watching. (electronic music)

>> From the Aria resort in Las Vegas it's theCUBE. Covering AWS marketplace. Brought to you by Amazon web services. >> Hey everybody, Jeff Frick here with theCUBE. We are kicking off AWS re:Invent, I don't know how many people are here, I'm guessing 60, could be 70, I don't know, there's a lot of people here in Vegas and we're excited. We'll be here for nine days of continuous coverage spread out over three calendar days, and we're kicking it of tonight. We're at the AWS Marketplace and service catalog experience here at the Quad over at the Aria, so stop on by, there's a lot of cool things going on, and we're excited to have a CUBE alumni on to kick things off. He's Sahir Azam, the SVP of Cloud from MongoDB. It's great to see you. >> Thank you Jeff, great to be here, exciting week coming up at AWS re:Invent. >> Are you ready? >> I think I am ready. It's going to be a long week in Vegas, but it'll be a good week. >> All I could think was all those posts before we got started, said how to plan your time at re:Invent, >> They all say drink a lot of water. >> Drink a lot of water, stay hydrated. So we last caught up at Summit in New York City, I believe. >> Yeah AWS Summit in New York. >> So that was last summer, so how have things been going since then? >> Things have been great, obviously, the business is doing really well, especially our cloud products MongoDB Atlas, and MongoDB stitch have been an absolute rocket ship for the company and that's why we're here, is just really help the community, and drive even more adoption of our technologies in the market. >> So is that a big strategic, I mean obviously, it was a big strategic move for you guys inside, but I'm just curious some of the thought process behind, you know, offering a database as a service via a partner like Amazon. What were some of the things you were thinking about, and how's it kind of turned out based on what your expectations were? >> Sure, yeah, I mean I think, if you look at just overall adoption of MongoDB, obviously you know, we're one of the most widely adopted databases in the world, given we're open source, and really a pioneer in modern non-relational databases. >> Right. >> We've always been heavily used in AWS, even from the early days, nine or 10 years ago and in many ways we feel like we grew up in the cloud, as a company, given just our technology and adoption in that marketplace. Now, what's changed is I think probably, five years ago or so, we really started to hear customers say, you know we really want to get out of the business of operationalizing and securing, and managing these databases, and would rather you give us the same technology, the database we love but deliver it as a service on our cloud platform of choice. So we started on a project internally, to build MongoDB Atlas, which is now available in 15 plus regions on AWS, as well as other cloud platforms as a global database as a service, to help those customers move even faster >> Right >> with MongoDB. >> And it's been about a year right, since you since you released it? >> It's been about three years for MongoDB Atlas, but especially in the last year we've started actually selling out was through the AWS marketplace. >> Right, right. >> Which is really fantastic. >> So how does the marketplace change? I mean obviously, Amazon's got a great scale, and it's a nice sales force, sales presence for you to leverage so, how has that relationship gone? >> Yeah, it's gone really well actually, and especially in large enterprises. I mean, we have large automotives, we've got manufacturers, we've got you know telcos, that have sort of all procured our technolog6y through the AWS marketplace. And I think the benefit for us as a partner, really comes in two ways, first and foremost, its awareness, there are definitely some AWS customers that find their technologies by searching on it in the marketplace and when we pop up, and say okay great this is the databases service from the people behind MongoDB. That instantly just drives our awareness up, and then secondly, it drives really good alignment between our sales teams and Amazon sales team. So the AWS sales force is now aligned and incented to work with us on driving joint opportunity for MongoDB, and now Amazon customers. >> So is there a lot of joint, kind of opportunities that you guys are working together? >> Yup. >> I guess my perception would be that more the marketplace is, you know I find it, I order it, I install it, versus more kind of a joint enterprise sale, but maybe that's not. >> For us it's actually been really interesting on the joint enterprise sale, where it's been, you know they're really that high touch model because it's beneficial for customers to be able to buy their technology through the marketplace, and it's also beneficial for our go-to-market, and our sales teams to be aligned and not feel like we're competing but are actually driving an outcome together for the customer. >> Right, so partnering with Amazon's been a good experience, I know a lot of people are kind of afraid, do we to be partner with these guys, are they big, are they going to you know roll up our functionality? But you guys had a great experience. >> Yeah, I mean the reality is we there are definitely database technologies from Amazon that we compete with. But that's true of probably every technology vendor, and where there are places for us to work together, and deliver real customer value, I mean we're the most widely adopted modern, non-relational kind of database on the planet. >> Right, right. >> So Amazon probably sees that demand, and it's been a good working relationship through the marketplace team, especially at Amazon. >> Good, so I wonder if you can share some other trends you've seen in the marketplace, especially as you said you guys are doing a lot of joint customer activity, what are some of the things you're picking up on, what are you hearing out on the streets? >> Sure I definitely think server list continues to rise. Right, this past year with G8 MongoDB Stitch, which is our server list platform that makes it really easy to extend the power of the database all the way through mobile devices, client applications, and really have a data architecture and not just think of Mongo as something that's used on the backend, so we've been seeing quite a bit of adoption of that platform, and in particular for use cases where MongoDB Atlas is used with complimentary AWS services. So if you want to use AWS Lambda with a MongoDB database, the best way to do so is with Stitch. You want to tie you know Kinesis and streaming technologies into a database for MongoDB, Stitch makes those integrations natively in these other AWS services really easy. >> Right, so I'm curious get your perspective on kind of what percentage, don't share anything you're not supposed to share, of the sales on these things are, new kind of projects inside these enterprises, versus people doing migrations, because there's always this big debate right on legacy? You know you're going to lift and shift, and move it all, versus let that stuff just do what it does, and really the opportunities on Greenfield. >> Yeah, I think, it's probably hard to quantify, but we certainly see a few different patterns. First and foremost, there's like large enterprises that are lifting and shifting, and migrating those applications from on-premises data centers and into the cloud. And really what we see is an opportunity, not just to lift and shift, and manage things the same expensive slow way, but to actually modernize at time of migration, as well. So you can adopt the benefits of a platform as a service, or a database a service like ours, while you move into the cloud. So that helps customers move faster and operate in a much more economical way. So I think that's sort of one piece of it, and then of course there's all sorts of new modern applications, whether it be Connected Car or IOT platforms, modern mobile applications, we're seeing a fair share of like new, fancy applications being built, as well. We definitely see both, and I think for us, one of the things that's unique is given there's been so much MongoDB adoption in AWS, we're seeing a migration of customers that want to get out of the business of running the database, and want to have us manage it for them in the form of MongoDB Atlas. There's that third camp of people are already in Amazon, using MongoDB, but are now saying I want to move it into Atlas because it provides a much better way, and in fact, it's probably the best way to run MongoDB in the cloud. >> Right, right, it makes a ton of sense. I'm curious I'm the first one though, when you talk about modernizing while you're lifting and shifting, or while you're shifting over from legacy infrastructure, what are the key things without doing a complete rewrite, that people can do kind of a modernization of the application, 'cause that's kind of an interesting concept? >> I think it's two things, there are certain applications that people don't want to touch and change that much, and those are probably good candidates to lift and shift, and try to minimize the amount of change on. But frankly those are oftentimes not the most strategic applications anymore, they might be important to keep the lights on, but they're not the ones that are driving the customer experience or driving the revenue, you know new opportunities for businesses. Many of those applications are actually being kind of decomposed from monolithic old technology stacks and legacy tools to more modern micro services based architectures, and what we're seeing, is oftentimes the trigger for that modernization is a cloud migration. So in many ways what we're saying is, get off of a legacy relational database technology, move to the cloud, but don't now operate it the same way you always have, actually consume it as a service, and that's what's really going to unlock all that developer velocity, the elasticity, the cost savings people expect from the cloud. >> Right, so is the the database really the key piece for kind of a modernization effort, without rewriting the entire application? >> I think it's one of the most important pieces, for sure. I mean we like to say that the database, in many ways, is the heart of the application, because an application without data is really sort of generic and useless. So it is definitely one of the more complicated areas, and that's why we spend so much time with customers, building technology that makes it easier for them to modernize, leverage new capabilities, even if it's only new features in an application, versus a rewrite of the whole old model right with the block. >> Alright, Sahir, I think they open the doors, I think AWS is coming in. >> The rush is coming in. It's officially underway, so I know you got a busy week, I got a busy week. >> Likewise. >> Thanks for taking a few minutes of your time. >> Absolutely. >> And stopping by. >> Yeah great to see you. >> Alright, great to see you. >> Alright, thanks for stopping by. He's Sahir, I'm Jeff, you're watching theCUBE, we're at the AWS marketplace and service catalog experience, at the Aria, stop on by, see ya. (dance music)

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and it's ecosystem partners. >> Welcome back to theCUBE. We are continuing our coverage of VMworld 2018 day 3. I'm Lisa Martin, with two very stylish men next to me. I'm quite impressed. Dave Vellante, my esteemed co-host. >> Oh shucks. >> Rocking the salmon, King Salmon Vellante. And The Zog is back, Eric Herzog. Great to have you back. I was looking at you on Twitter and you have been on theCUBE 17 times. Is this 18 or 19? >> You know, I think Dave said I was on one of the very first CUBEs way back in 2010. So I've been on a few. >> That's a whole other criteria of VIP level. Well thank you for coming back. You have been, not only is he, you can't do a CUBE without Eric Herzog. You've been everywhere all over VMworld. I saw you're speaking at IBM booth on VMware and IBM, you're at Cisco, you're giving sessions. How do you fit it all in and still have time for us? >> Well, I always make time for theCUBE. >> Always? Thank you, thanks for that. >> Always make time for you guys. Love talking to CUBE. You guys have been very helpful. We appreciate everything that you do. Love doing shows, love 'em. I may be 60 years old, but I'm really 18 down underneath, so if I only sleep three hours a night, not a problem. >> What do you love about them? I mean, is it? >> Number one is meeting customers. Customers and channel partners, right? Well, all of the employees of all the various companies here get a paycheck from whoever that may be, me, IBM, someone from other companies, people from VMware. That's not who pays your salary. It's the end-users and the channel partners, if they buy through the channel. They're the ones that really pay your salary. So being close to the customers and the partners is number one. Second thing, of course, is seeing all the cool technology. You know, seeing what's going on, what's hot, what can we leverage from our perspective, what can we tie ourselves to. So for example, the hot things, that IBM's really been doing from a storage perspective. Cloud and modern data protection. Those are the two big things we've been focused on for the last couple of years. And how do we integrate our storage solutions and our modern data protection with cloud infrastructure, and then also how do we, if you're not in the cloud, how do we help customers protect their data better in a modern way and reuse their secondary data, instead of making 27,000 copies of the same data. >> So when theCUBE first started at VMworld, modern data protection at the time was dealing with the lack of physical resources, 'cause you went from 10 servers down to one, and you didn't have all that excess capacity to do a run up back up job anymore. Today, modern data protection is all around cloud and multi-cloud and software defined, so I wonder if you can help us sort of paint a picture of what modern data protection is for IBM? >> Sure, I think there's a couple, couple aspects too. So, first of all, you have to support the cloud, and that's two ways. So for us, several of our backup products are used by cloud service providers. In some cases they use our name, and say, "Featuring IBM Spectrum Protect or Spectrum Protect Plus." Other cases, they have their own brand but it's our software underneath the hood so that if the end user is backing up to their cloud, they're actually using our software. So that's item number one. The second thing is you need to make sure that your traditional storage software can TEAR to the cloud, can migrate data to the cloud, can transparently move data to the cloud in an automated fashion using AI. So using artificial intelligent when the data's hot if you connote a target, and that target could be a cloud, and when the data's hot it TEARs the data to the cloud. Sorry, when it's cold. When it's hot it pulls it back in and that needs to be all automated through AI base. So we've done both, we have our backup software which is available from several cloud providers as a backup as a service, we also offer it through the cloud so IBM Cloud actually sells spectrum protect backup as a service solution All of our primary storage software and even our spectrum scale software can automatically TEAR data to a cloud target device. >> Eric I got to ask you so TEARing used to be predominantly, correct me if you disagree but, it used be a one way trip to the bit-bucket. You just described going there and coming back. Has cloud changed that because of big data, analytics? Where people want to pull back data increasingly? >> So I think of a couple of things. So first of all, there's no doubt that the world is data driven. The most valuable asset isn't gold, it's not silver, it is absolutely not oil, it's not diamonds. It is data. And it doesn't matter whether you're one of the largest banks in the world, you're in manufacturing, you're in the government, or whether you're Herzog's barn grill. The data is your most valuable asset. What you do with your customer data, how you manage your business, what you do with your supply chain if your a services company, how are you servicing, what are you charging, what are you billing, all of that is the most critical thing that you have. So in a data driven world, its critical that you use the data. And that also means that because of valued data, when you backup the data or you snapshot or replicate the data, you now created a secondary copy. Well what if you could use it to do tests? What if you could use it to do big data analytics? What if you could use it for DevOps? So instead of making one copy for tests, one copy for disaster recovery, one copy for this, and have basically a plethora of copies all over the place, with what we've provided in modern data protection, you can use a backup, you can use a snap or a replica, and you can use that to do tests or development or to do big data analytics. And using that one copy not making multiple copies. So that's- >> I just want to pick up on something you said there's going to be some folks in our audience like, "yeah yeah we hear that data is more valuable than oil or more valuable than gold, et cetera, more valuable than platinum." There's evidence, if you look at the market value of the top five companies, Apple, Facebook, Microsoft, Google, and Amazon, they've surpassed the banks, they've surpassed the energy companies, and I would argue its cuz of data. People are recognizing that they're data companies, you agree? >> But if you look at that name the only one that actually builds anything of substance, as a fair amount of their volume of revenue, is Apple. >> Is Apple, right. >> Amazon doesn't, they ship stuff. Facebook clearly doesn't, Google has a few things but not really builds stuff its really about the data. Absolutely and if your a more traditional company like a bank or someone building the table. Whoever builds this table if they have their act together and they're using that data right, they're building the table cheaper than anyone else, they're shipping it to theCUBE cheaper than anyone else could ship it to you. They got more colors because they know what their doing. And they ship you the right color table and they don't screw it up and send you a black table when you want it this color table because black won't show up on theCUBE very well. The more you do that the more money you make. Even something as simple as a table manufacturer. And that's all about the data and how you use that data. >> So Eric you love talking with customers which is great as the CMO for IBM storage. Got to talk to those customers. Let's talk about how you're seeing customers take the efficiencies of what IBM is doing with data protection, storage, et cetera. to be able to harness the power of AI, the superpowers that Pat Gelsinger talked about on Monday, and transform their businesses. Give us some of your favorite customer examples where its really revolutionary. >> So we had a great example today, we did a panel with a bunch of end users as part of the show agenda. And one of the customers is a provider of softwares of service to universities and schools. 45,000 customers between the universities, junior colleges, schools districts, et cetera. In North America so Canada and the U.S. And they are doing softwares of service so for them performance is critical, they can't go down. All of the college bookstores, if you go into a college bookstore, all of the infrastructure behind that is them. So they're called Follet. So a couple of things, one because they're doing softwares of service and managing all that. Its critical, can't go down. Got to be available, it's got to be performant, it's got to be resilient, it's got to be reliable. So that's how the storage melds in. From modern data protection the way it melds in is how many books did Dave buy? What did Eric buy? Oh is Dave buying a used book? Or is Eric buying a new book? Okay say we know that the propensity is certain of members of the community. I went to UC Davis, University of California Davis, are going to buy used books, Dave, whereas Herzog's going to buy new. They can figure that out, how many used books they need, how many new books they need, that's all about efficiency and how they make more money. What are the store hours? Certain universities it's this, other universities it's that. What do they do in the winter time? At UC Davis you can go in the winter time, I know you went to school in Boston its probably snowing, no one's going in the bookstore in the wintertime. >> Trend towards book rentals, how do we capitalize on that? >> That's all they do. One of the things they talked about was how they always have to protect that data and back it up. The other thing they talked about was they have to assume a lot of capacity. So what they do is they bought assuming they would have to refresh in 18 months. And because our storage arrays have a ton of different data reduction technology whether that be block, D2, compression, et cetera. And they have petabytes of data. Petabytes. 12 Petabytes. They've actually calculated it out they won't need to buy new storage for 36 months instead of 18 so they just saved on CapX. Through the intelligence of the storage. So in that case you've got both modern data protection and you've got a storage message. One of our other customers who's a public reference, not here at the show, which is a hospital, they were backing up all their data, both cloud and on premise with our backup software, and they went down and their entire system went down and they didn't lose one stitch of data and its a hospital. It's a teaching hospital, think they're in Pennsylvania, and in the public reference in the video he said, "and we went down and off that backup we were able to get all of the data back. We didn't lose any patient data, we didn't lose any research data, we didn't lose any billing data, if you break your arm they do bill you, they didn't lose anything." >> That's not just money, that's lives so that's huge. >> Absolutely. >> I want to ask you about you know that table example you were giving, and we were talking about the big five companies in terms of market cap being data orientated. There seems to be a gap between those sort of traditional companies and those data companies and that gap tends to be the data is often is often in silos its human expertise or expertise around a bottling plant or the manufacturing plant or whatever it is versus a data model with humans who understand how to leverage that data. Do you see, whether its through new data protection techniques or other storage techniques that IBM is working on, ways to help customers break down those data silos so they can become more digital and be able to take advantage of data? >> So I think there's a couple of things. So first of all at the very tactical level we provide this automated IA based data TEARing. We can tear from anything to anything so we can take data from an IBM array and TEAR it to an EMC array. We can take data from an EMC array and TEAR it to a net app array. A net app array to a Tachi array, an HP array back to our array, so we can do this transparent data move based on hot and cold. Not only does that allow you to control CapX and OpX you can move the data from array to array, and once you move that data set it might be working that other array could be hooked up to a different set of servers through the SAN that's running a different workload and then takes that dataset and use it with that other piece of software out on the server side. So that's item number one. Item number two is IBM not just in the storage but overall has a global program where IBM is promoting, through universities all over the world, data scientists. Part of that is training data scientists not only how to do the science of data and analyzing data and mining data and doing it, but to break down those walls. The value is more there. And we also have from a storage perspective some products are spectrum scale products, one of our customers who's one of the largest banks in the world they run 300,000 servers attached to a giant spectrum scale repository, petabytes and petabytes, and they do real time data analytics to see if Dave Vellante or Lisa's credit card was stolen. >> Thank you! >> Oh yes, thank you! >> So that's real world analytics they run but they need petabytes of data. And then with our IBM cloud object storage technology where we have several customers at the exabyte level in production with an exabyte of data, you put the data out when its cold but guess what, if you want to mine it you might want to pull it back and guess what, you can TEAR data from spectrum scale to IBM cloud object storage and then spectrum scale can pull it back in to do the big data analytic workloads. >> And that AI you're using is it heavy open source? Is there a little bit of Watson sprinkled in there? >> It's stuff the storage division developed years ago and then has peppered in the AI based technology into that software to determine when the dataset is hot or cold and then move it back or forth. We also do the old style, so if you go back 10 years ago, the automation of storage was policy based. So we had it way back when which was if the data is 30 days old move it to this array. >> The old HSM kind of... >> Yeah and it was automated so once it hit 30 days, but now what we've done is, we started with that, what I would call automation, and now we've moved that to AI. And by the way, if you still want to do it the old way and say move this data when its 60 days old, you can still do that. But the modern way is let the storage figure out for you and move it back and forth whether it be to the cloud or whether it be on premises. >> So it's intelligent hierarchical storage management? So if the characteristics change the system knows what to do as opposed to- >> So when it's hot it'll pull the data back into flash, for example, when its cold it'll put it out to cloud, it'll put it out to tape or it'll put it out to slow hard drives, either way. >> Alright Eric, so we're almost out of time here. You've been at IBM a long time, IBM's been around a long time, you said you even have customers at exabyte scale. I'm hearing heterogeneity, customer choice, but if I'm a small hospital in the middle of America and I have choice with data protection vendors, storage vendors, some smaller than IBM that might be able to move faster, what are the top three differentiators of why I would want to go with IBM's storage solutions? >> Sure so the first thing is our broad portfolio. Whether it be file block or object, whether it be modern data protection, whether it be archiving if you still want to use tape, we're the number one provider of tape in the world and we sell gobs of it to the web scale guys. >> Of course you do. >> They're the guys that buy it. >> Cuz its cost effective. >> So we've got one throat to choke, all of it talks to each other, and happens to work with all the cloud vendors not just IBM cloud. We work with Amazon, we work with Microsoft, we work with Google, and we work with IBM's own cloud. So we can work with anything. That's out of mind. Second thing, for smaller shops we have a network of business partners all over the world, some of them even deal with the big global Fortune 500 and others deal with small accounts. And then really the third thing is that IBM makes sure that our stuff works with everyone else's stuff. Whether that be cloud, our spectrum tech software which has been around for years and is the leading enterprise backup package, the bulk of what it backs up is not IBM storage. The vast bulk of it is from two of the competitors on the floor of this show, they also back up our stuff too. And we backup everyone's. There's probably 20 storage vendors we backup every one of their data. So if someone buys storage from XYZ, call me, we can back it up. If someone buys it from one of the big competitors we back it up, from us we back it up. So the fact that our software works with everyone's gear is of an advantage for both the small shop and the big shop. We make sure that our software, whether its embedded in our arrays or whether we sell it as just a pieces storage software and we are the number one storage software provider on the planet as well, we can meet the needs of any company big or small because we have this flexibility of working with our stuff and working with everybody else stuff and most of the other guys don't do that. If its a small shop their stuff usually only works with their stuff. >> And from a support perspective, you play with everybody? >> Global network. I mean we're known for our support whether it be IBM direct or what we do with our partners all the partners are certified, its a big certification process, and if they can't certify the product they can't sell IBM's stuff. That's just how we operate. Other people, if they can move a lot of boxes but they don't have anyone pick up the phone or can come out to Dave's house to install, they let them sell, we don't do that at IBM. We don't use those box mover types we go for guys that add value and know how to work with the cloud, know how to do hybrid cloud. One of our resellers designed a Watson based AI system that's used in bottle factories. Packaging. Beer, soda, milk, and it can figure out if its full or not full, if the bottle or can or carton is damaged. And they used Watson to do it. Now they're regular resell. They resell all the storage, they resell our power, they resell mainframe, but they've gone into the software development side using this Watson thing and they're selling a full solution with the software included to bottling plants all over the world. >> Wow, Eric. This has been a super charged conversation. Thanks for stopping by and talking with Dave and me about not just your excitement about talking with customers but really how IBM is really empowering customers of any size worldwide to succeed. We know we'll see you again soon but thanks for stopping by a couple of times this week. >> Great well thank you. Thank you, really appreciate the time. >> And the outfit choices are just on point guys, you blend well too. For Eric, Dave Vellante, I am Lisa Martin, you're watching theCUBE live from VMworld 2018 day 3. Stick around, we'll be back with our next guest after a short break. (electro music)

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and it's ecosystem partners. >> Welcome back to theCUBE. We are continuing our coverage of VMworld 2018 day 3. I'm Lisa Martin, with two very stylish men next to me. I'm quite impressed. Dave Vellante, my esteemed co-host. >> Oh shucks. >> Rocking the salmon, King Salmon Vellante. And The Zog is back, Eric Herzog. Great to have you back. I was looking at you on Twitter and you have been on theCUBE 17 times. Is this 18 or 19? >> You know, I think Dave said I was on one of the very first CUBEs way back in 2010. So I've been on a few. >> That's a whole other criteria of VIP level. Well thank you for coming back. You have been, not only is he, you can't do a CUBE without Eric Herzog. You've been everywhere all over VMworld. I saw you're speaking at IBM booth on VMware and IBM, you're at Cisco, you're giving sessions. How do you fit it all in and still have time for us? >> Well, I always make time for theCUBE. >> Always? Thank you, thanks for that. >> Always make time for you guys. Love talking to CUBE. You guys have been very helpful. We appreciate everything that you do. Love doing shows, love 'em. I may be 60 years old, but I'm really 18 down underneath, so if I only sleep three hours a night, not a problem. >> What do you love about them? I mean, is it? >> Number one is meeting customers. Customers and channel partners, right? Well, all of the employees of all the various companies here get a paycheck from whoever that may be, me, IBM, someone from other companies, people from VMware. That's not who pays your salary. It's the end-users and the channel partners, if they buy through the channel. They're the ones that really pay your salary. So being close to the customers and the partners is number one. Second thing, of course, is seeing all the cool technology. You know, seeing what's going on, what's hot, what can we leverage from our perspective, what can we tie ourselves to. So for example, the hot things, that IBM's really been doing from a storage perspective. Cloud and modern data protection. Those are the two big things we've been focused on for the last couple of years. And how do we integrate our storage solutions and our modern data protection with cloud infrastructure, and then also how do we, if you're not in the cloud, how do we help customers protect their data better in a modern way and reuse their secondary data, instead of making 27,000 copies of the same data. >> So when theCUBE first started at VMworld, modern data protection at the time was dealing with the lack of physical resources, 'cause you went from 10 servers down to one, and you didn't have all that excess capacity to do a run up back up job anymore. Today, modern data protection is all around cloud and multi-cloud and software defined, so I wonder if you can help us sort of paint a picture of what modern data protection is for IBM? >> Sure, I think there's a couple, couple aspects too. So, first of all, you have to support the cloud, and that's two ways. So for us, several of our backup products are used by cloud service providers. In some cases they use our name, and say, "Featuring IBM Spectrum Protect or Spectrum Protect Plus." Other cases, they have their own brand but it's our software underneath the hood so that if the end user is backing up to their cloud, they're actually using our software. So that's item number one. The second thing is you need to make sure that your traditional storage software can TEAR to the cloud, can migrate data to the cloud, can transparently move data to the cloud in an automated fashion using AI. So using artificial intelligent when the data's hot if you connote a target, and that target could be a cloud, and when the data's hot it TEARs the data to the cloud. Sorry, when it's cold. When it's hot it pulls it back in and that needs to be all automated through AI base. So we've done both, we have our backup software which is available from several cloud providers as a backup as a service, we also offer it through the cloud so IBM Cloud actually sells spectrum protect backup as a service solution All of our primary storage software and even our spectrum scale software can automatically TEAR data to a cloud target device. >> Eric I got to ask you so TEARing used to be predominantly, correct me if you disagree but, it used be a one way trip to the bit-bucket. You just described going there and coming back. Has cloud changed that because of big data, analytics? Where people want to pull back data increasingly? >> So I think of a couple of things. So first of all, there's no doubt that the world is data driven. The most valuable asset isn't gold, it's not silver, it is absolutely not oil, it's not diamonds. It is data. And it doesn't matter whether you're one of the largest banks in the world, you're in manufacturing, you're in the government, or whether you're Herzog's barn grill. The data is your most valuable asset. What you do with your customer data, how you manage your business, what you do with your supply chain if your a services company, how are you servicing, what are you charging, what are you billing, all of that is the most critical thing that you have. So in a data driven world, its critical that you use the data. And that also means that because of valued data, when you backup the data or you snapshot or replicate the data, you now created a secondary copy. Well what if you could use it to do tests? What if you could use it to do big data analytics? What if you could use it for DevOps? So instead of making one copy for tests, one copy for disaster recovery, one copy for this, and have basically a plethora of copies all over the place, with what we've provided in modern data protection, you can use a backup, you can use a snap or a replica, and you can use that to do tests or development or to do big data analytics. And using that one copy not making multiple copies. So that's- >> I just want to pick up on something you said there's going to be some folks in our audience like, "yeah yeah we hear that data is more valuable than oil or more valuable than gold, et cetera, more valuable than platinum." There's evidence, if you look at the market value of the top five companies, Apple, Facebook, Microsoft, Google, and Amazon, they've surpassed the banks, they've surpassed the energy companies, and I would argue its cuz of data. People are recognizing that they're data companies, you agree? >> But if you look at that name the only one that actually builds anything of substance, as a fair amount of their volume of revenue, is Apple. >> Is Apple, right. >> Amazon doesn't, they ship stuff. Facebook clearly doesn't, Google has a few things but not really builds stuff its really about the data. Absolutely and if your a more traditional company like a bank or someone building the table. Whoever builds this table if they have their act together and they're using that data right, they're building the table cheaper than anyone else, they're shipping it to theCUBE cheaper than anyone else could ship it to you. They got more colors because they know what their doing. And they ship you the right color table and they don't screw it up and send you a black table when you want it this color table because black won't show up on theCUBE very well. The more you do that the more money you make. Even something as simple as a table manufacturer. And that's all about the data and how you use that data. >> So Eric you love talking with customers which is great as the CMO for IBM storage. Got to talk to those customers. Let's talk about how you're seeing customers take the efficiencies of what IBM is doing with data protection, storage, et cetera. to be able to harness the power of AI, the superpowers that Pat Gelsinger talked about on Monday, and transform their businesses. Give us some of your favorite customer examples where its really revolutionary. >> So we had a great example today, we did a panel with a bunch of end users as part of the show agenda. And one of the customers is a provider of softwares of service to universities and schools. 45,000 customers between the universities, junior colleges, schools districts, et cetera. In North America so Canada and the U.S. And they are doing softwares of service so for them performance is critical, they can't go down. All of the college bookstores, if you go into a college bookstore, all of the infrastructure behind that is them. So they're called Follet. So a couple of things, one because they're doing softwares of service and managing all that. Its critical, can't go down. Got to be available, it's got to be performant, it's got to be resilient, it's got to be reliable. So that's how the storage melds in. From modern data protection the way it melds in is how many books did Dave buy? What did Eric buy? Oh is Dave buying a used book? Or is Eric buying a new book? Okay say we know that the propensity is certain of members of the community. I went to UC Davis, University of California Davis, are going to buy used books, Dave, whereas Herzog's going to buy new. They can figure that out, how many used books they need, how many new books they need, that's all about efficiency and how they make more money. What are the store hours? Certain universities it's this, other universities it's that. What do they do in the winter time? At UC Davis you can go in the winter time, I know you went to school in Boston its probably snowing, no one's going in the bookstore in the wintertime. >> Trend towards book rentals, how do we capitalize on that? >> That's all they do. One of the things they talked about was how they always have to protect that data and back it up. The other thing they talked about was they have to assume a lot of capacity. So what they do is they bought assuming they would have to refresh in 18 months. And because our storage arrays have a ton of different data reduction technology whether that be block, D2, compression, et cetera. And they have petabytes of data. Petabytes. 12 Petabytes. They've actually calculated it out they won't need to buy new storage for 36 months instead of 18 so they just saved on CapX. Through the intelligence of the storage. So in that case you've got both modern data protection and you've got a storage message. One of our other customers who's a public reference, not here at the show, which is a hospital, they were backing up all their data, both cloud and on premise with our backup software, and they went down and their entire system went down and they didn't lose one stitch of data and its a hospital. It's a teaching hospital, think they're in Pennsylvania, and in the public reference in the video he said, "and we went down and off that backup we were able to get all of the data back. We didn't lose any patient data, we didn't lose any research data, we didn't lose any billing data, if you break your arm they do bill you, they didn't lose anything." >> That's not just money, that's lives so that's huge. >> Absolutely. >> I want to ask you about you know that table example you were giving, and we were talking about the big five companies in terms of market cap being data orientated. There seems to be a gap between those sort of traditional companies and those data companies and that gap tends to be the data is often is often in silos its human expertise or expertise around a bottling plant or the manufacturing plant or whatever it is versus a data model with humans who understand how to leverage that data. Do you see, whether its through new data protection techniques or other storage techniques that IBM is working on, ways to help customers break down those data silos so they can become more digital and be able to take advantage of data? >> So I think there's a couple of things. So first of all at the very tactical level we provide this automated IA based data TEARing. We can tear from anything to anything so we can take data from an IBM array and TEAR it to an EMC array. We can take data from an EMC array and TEAR it to a net app array. A net app array to a Tachi array, an HP array back to our array, so we can do this transparent data move based on hot and cold. Not only does that allow you to control CapX and OpX you can move the data from array to array, and once you move that data set it might be working that other array could be hooked up to a different set of servers through the SAN that's running a different workload and then takes that dataset and use it with that other piece of software out on the server side. So that's item number one. Item number two is IBM not just in the storage but overall has a global program where IBM is promoting, through universities all over the world, data scientists. Part of that is training data scientists not only how to do the science of data and analyzing data and mining data and doing it, but to break down those walls. The value is more there. And we also have from a storage perspective some products are spectrum scale products, one of our customers who's one of the largest banks in the world they run 300,000 servers attached to a giant spectrum scale repository, petabytes and petabytes, and they do real time data analytics to see if Dave Vellante or Lisa's credit card was stolen. >> Thank you! >> Oh yes, thank you! >> So that's real world analytics they run but they need petabytes of data. And then with our IBM cloud object storage technology where we have several customers at the exabyte level in production with an exabyte of data, you put the data out when its cold but guess what, if you want to mine it you might want to pull it back and guess what, you can TEAR data from spectrum scale to IBM cloud object storage and then spectrum scale can pull it back in to do the big data analytic workloads. >> And that AI you're using is it heavy open source? Is there a little bit of Watson sprinkled in there? >> It's stuff the storage division developed years ago and then has peppered in the AI based technology into that software to determine when the dataset is hot or cold and then move it back or forth. We also do the old style, so if you go back 10 years ago, the automation of storage was policy based. So we had it way back when which was if the data is 30 days old move it to this array. >> The old HSM kind of... >> Yeah and it was automated so once it hit 30 days, but now what we've done is, we started with that, what I would call automation, and now we've moved that to AI. And by the way, if you still want to do it the old way and say move this data when its 60 days old, you can still do that. But the modern way is let the storage figure out for you and move it back and forth whether it be to the cloud or whether it be on premises. >> So it's intelligent hierarchical storage management? So if the characteristics change the system knows what to do as opposed to- >> So when it's hot it'll pull the data back into flash, for example, when its cold it'll put it out to cloud, it'll put it out to tape or it'll put it out to slow hard drives, either way. >> Alright Eric, so we're almost out of time here. You've been at IBM a long time, IBM's been around a long time, you said you even have customers at exabyte scale. I'm hearing heterogeneity, customer choice, but if I'm a small hospital in the middle of America and I have choice with data protection vendors, storage vendors, some smaller than IBM that might be able to move faster, what are the top three differentiators of why I would want to go with IBM's storage solutions? >> Sure so the first thing is our broad portfolio. Whether it be file block or object, whether it be modern data protection, whether it be archiving if you still want to use tape, we're the number one provider of tape in the world and we sell gobs of it to the web scale guys. >> Of course you do. >> They're the guys that buy it. >> Cuz its cost effective. >> So we've got one throat to choke, all of it talks to each other, and happens to work with all the cloud vendors not just IBM cloud. We work with Amazon, we work with Microsoft, we work with Google, and we work with IBM's own cloud. So we can work with anything. That's out of mind. Second thing, for smaller shops we have a network of business partners all over the world, some of them even deal with the big global Fortune 500 and others deal with small accounts. And then really the third thing is that IBM makes sure that our stuff works with everyone else's stuff. Whether that be cloud, our spectrum tech software which has been around for years and is the leading enterprise backup package, the bulk of what it backs up is not IBM storage. The vast bulk of it is from two of the competitors on the floor of this show, they also back up our stuff too. And we backup everyone's. There's probably 20 storage vendors we backup every one of their data. So if someone buys storage from XYZ, call me, we can back it up. If someone buys it from one of the big competitors we back it up, from us we back it up. So the fact that our software works with everyone's gear is of an advantage for both the small shop and the big shop. We make sure that our software, whether its embedded in our arrays or whether we sell it as just a pieces storage software and we are the number one storage software provider on the planet as well, we can meet the needs of any company big or small because we have this flexibility of working with our stuff and working with everybody else stuff and most of the other guys don't do that. If its a small shop their stuff usually only works with their stuff. >> And from a support perspective, you play with everybody? >> Global network. I mean we're known for our support whether it be IBM direct or what we do with our partners all the partners are certified, its a big certification process, and if they can't certify the product they can't sell IBM's stuff. That's just how we operate. Other people, if they can move a lot of boxes but they don't have anyone pick up the phone or can come out to Dave's house to install, they let them sell, we don't do that at IBM. We don't use those box mover types we go for guys that add value and know how to work with the cloud, know how to do hybrid cloud. One of our resellers designed a Watson based AI system that's used in bottle factories. Packaging. Beer, soda, milk, and it can figure out if its full or not full, if the bottle or can or carton is damaged. And they used Watson to do it. Now they're regular resell. They resell all the storage, they resell our power, they resell mainframe, but they've gone into the software development side using this Watson thing and they're selling a full solution with the software included to bottling plants all over the world. >> Wow, Eric. This has been a super charged conversation. Thanks for stopping by and talking with Dave and me about not just your excitement about talking with customers but really how IBM is really empowering customers of any size worldwide to succeed. We know we'll see you again soon but thanks for stopping by a couple of times this week. >> Great well thank you. Thank you, really appreciate the time. >> And the outfit choices are just on point guys, you blend well too. For Eric, Dave Vellante, I am Lisa Martin, you're watching theCUBE live from VMworld 2018 day 3. Stick around, we'll be back with our next guest after a short break. (electro music)

>> It's The Cube, covering AWS Summit New York 2018. Brought to you by Amazon Web Services and its ecosystem partners. >> Hey, welcome back everyone. This is The Cube's live coverage here in New York City with Amazon Web Services AWS Summit 2018. I'm here with Jeff Frick, I'm John Furrier. Our next guest is Sahir Azam, Senor Vice President of MongoDB for the Cloud products. Mongo's been very successful. Everyone knows it in the developer community. If you've done anything building Agile, Mongo's been there. Great to have you on. >> Happy to be here, thanks guys. >> So Mongo's been one of those success stories where, if you look at the LAMP stack days, and you now look at Agile, it's been the database for everybody. It's been scaling up nicely. Some people were saying, oh Mongo doesn't scale. Well, hello Cloud. You guys have done very, very well. Amazon's a big part of what you guys are doing. What's new with your business and The Cloud? >> It's been quite a story, to be quite honest. We were launched as an open source technology, just about 10 years ago, which was right around the time Amazon really came to market. So in many ways, we've always been well deployed, heavily used in The Cloud. If you look at the massive community phenomenon that is MongoDB, the majority of that actually sits in AWS. But the strategic sort of move that we made a couple years ago, based on customer input was, to start delivering MongoDB as a service, directly on Amazon Web Services. Now we're actually available in over 14 regions on AWS, and it's had a tremendous effect on our business. We launched it, obviously, with 0% of our revenue. It's now, two years later, 14% of our revenue, over 44 hundred customers, and it's just a rocket ship. >> It's such a great trajectory, but I want you to take a minute to explain the dynamics of the database market. Because clearly Amazon's always taking shots at Oracle, you get any chance it's always making fun of Oracle. Because you have the big old school database, but with IoT, databases are proliferating everywhere. And they're really critical part of Agile. How is the database landscape looking like, and how has Cloud taken it up a notch? How has it changed it? >> Yeah, definitely. I think there's sort of two angles I think we see that are really interesting. One is, I think the thing that always drove and still does drive the developer adoption among ODB, is the fact that it's much more natural for a developer to work in a document model. They think building an application, they're thinking about business objects. The user, an invoice, a product, and you can just map that so naturally as a developer in MongoDB, and that is just a much faster business innovation cycle than a traditional, relational database. And that will only grow as more and more organizations, even traditional organizations, start to build customer-facing applications, where their engineering teams now need to ship in an agile manner, pushing out new versions of their application weekly, or daily, instead of annually. So I think that's sort of fundamental. And in many ways, The Cloud accelerates that. Whether you look at the DevOps movement and what's happening there, we're seeing the shift where no one wants to spend the skillset and time to learn how to manage a distributed database system, or any database system, for that matter. They want to focus on writing compelling applications. So if we can deliver at a very economical price point and elastic service that then scales endlessly, it allow them to focus on their core business and us to focus on ours. >> And that's the benefit of The Cloud. But talk about this Atlas product, two years ago who had no customers. Now you have over 4,000 and growing. >> Correct. >> That's just plug and play off The Cloud? Order on the marketplace? How are the customers onboarding? >> There's multiple ways. We have certainly a very healthy self-service, direct-to-developer type of business, where they can go online, swipe a credit card, get started on our free tier, and start off with small development environments that are $10 a month, all the way through giant, globally distributed clusters that can scale an application to millions. So, that starts developer first. However, we're interestingly seeing an uptake of that, especially this year, even an enterprise, established, highly regulated accounts as well, where they have a massive Cloud migration happening in conjunction with Amazon, and they want to use MongoDB because the richness of our database. The ability to now buy through the marketplace and consume it as a service is really compelling. >> So you're curious about how your relationship with the customers changed when you went to as-a-service with the database. Was there significant change in that relationship? How does it change when you've got this ongoing, monthly billing activity? >> Definitely, great question. I think it changed interestingly. Obviously the financial model's different because it's a consumption based model, based on pay for what you use. So that's obviously very Cloud-centric, Cloud-native, that's more of the math side of things. What I think is more interesting is now, we're obviously managing the customer's mission-critical databases. So when they're buying into a technology like Atlas from us, or Stitch from us, it's no longer just choosing Mongo because it's a great product. Its' choosing Mongo because it's a company they trust to run a mission-critical application and scale it as a partner. So it's elevated the strategic nature of how we're used, as a modern, persistent store and database. As an alternative to Oracle is sort of one angle, but now to look at it as a trusted partner. Because frankly, there's a share of risk model that has to happen in a Cloud services model. And that's been the biggest dynamic that's elevated our standing in many of these accounts. >> I presume you see an increased trajectory. It's going to take an increasing share of your total business as you go forward. >> It was 14% last quarter, certainly it's a big focus of ours. It's growing over 400% per year from a scale point of view. So we're doubling down, no question. >> Take a minute to talk about MongoDB Stitch and the four components you guys have in there. What's relevant about that? Why is it important for MongoDB customers and potential customers? >> At the macro level, we're seeing the constant trend of developers wanting to be more productive and consume higher levels of abstractions, and they have to write less code. That's the macro reason why we built Stitch. Because it's always been our mission as a company, to empower developers and build great, amazing apps. But at a specific level, what's interesting is, now that we're in The Cloud, we can enable interesting functionality in a few ways. In one sense, many developers, many engineers, have been used to things like triggers in the relational world, meaning, you're watching for data changing and you want to execute some sort of action. So now we've brought triggers into the non-relational modern database world, which Stitch triggers. So now any change in a database in Atlas can trigger an integration into Amazon's Kinesis service, or dumping data into S3, a variety of different use cases, to enable real time, sort of reactive application. So that's sort of fundamental, that's number one. The second is, enabling client-side apps. Mobile applications, rich web applications, to have more enabling, faster technology. Because now the client app can interact with the database in a much richer way, with the secure model. The query anywhere service does exactly that. It brings the full power of Mongo all the way through the edge, all the way through the client-side application, with Mongo Mobile. So we're really extending our reach and architecture because fundamentally, what we're hearing from developers is, we want to work with MongoDB because it's the best way to work with modern data, but help me do that everywhere. >> It's like stitching together all the data. Jeff, we were just talking about on the IoT portion of our intro package, how, if you stitch it all together, you can really bring everything beautifully together. Because the operators are spending a lot of time wasted on brunt work and tasks that they don't want to do. And with The Cloud, I think this is one of the value propositions we're seeing this year become very clear. And sort of with the VMware relationship annoucement a couple years ago, you're going to hear about it at Google Next and some other Cloud conferences. The developers are king. The operator's still going to be an elevated role, they're not going away. The storage administrator becomes the IT Operations guy, so the operators and the developers are going to create a nice, symbiotic relationship. Is this is where Stitch hits home? >> It his home from a governance and security standpoint around that, as does Atlas, right? Because what we're seeing is the modern operators are saying, listen, it's not strategic for us to learn all the bits and bites of infrastructure management anymore, or database configuration management, whatever it might be. But it is strategic to say, what are the key services that we're going to partner with for the long term of this business, while protecting governance and risk, thinking about security, abstracting away any particular providers. We're definitely seeing an evolution in the traditional operations role, and then at the same time, a developer's influence is consistently increasing in the market. >> I want to get your thoughts on this. You've been an industry veteran for a while, going back to the old BMC days, or before that, looking at the early days, and when the tech stacks are pretty well understood. And certainly Mongo made their bones, early days with LAMP stack, early days with Open source, now certainly changed with Cloud. Looking back now and seeing what's happening now, a lot of people are reawakening to The Cloud. I was just talking to an investor in Silicon Valley, who was doing some work in China just five years, has kind of been out of the enterprise IT space, he's like, damn, the stack has changed significantly. What have you observed, how would you talk about the changes between just five, six years ago and today? From a stack standpoint, from a capability standpoint, from a critical architecture standpoint, what's your view? >> I think, first and foremost, we're seeing a shift in application architecture. We're seeing the idea of micro services, decomposed applications, decoupled components and functionality, that's only rising. And we're seeing that, interestingly, not only for new applications, but also legacy modernization of existing applications. So now, that's actually driving a change in our business. Instead of the shiny, new IoT apps or mobile apps or web apps, that Mongo's always been strong for, we're now seeing 30% of our business come from legacy application modernization to micro services. >> 30% of your business is modernizing legacy apps? >> Correct. >> Wow. >> As they want to drive faster developer productivity, better economics, obviously, of running that application and build it on a more modern platform and architecture. >> You put a container around Kubernetes, you can now bring them into a modern architecture without sunsetting them rapidly. You don't have to rip and replace. You can just let it take a natural lifecyle. >> Right. And we basically play with that in two ways. If you're in the public Cloud, there's a nice fit between Kubernetes wrapping all the different app components, making them abstracted, scalable, Atlas underneath this fluid data layer. Or, if a customer's their own data center trying to modernize their stack, standardizing on Kubernetes, we now integrate our IP around automation and management directly into Kubernetes. That was one of the big announcements we made a few weeks ago. >> That makes Mongo really more versatile than ever before. I think the database as a service proves that you can really see the value of how having not a one spot only in the stack you can sit down with Atlas and then provide agility. Is that what's going on? >> The key driver is always agility for us. And then there's, oh wow, there's a huge cost savings to this as well. Whether it be in terms of productivity, infrastructure cost, just because of the native architecture, so as we see more and more organization become software companies, effectively, as the saying goes, that's just been a huge tailwind to our business. >> So two final questions for me, and I'll Jeff ask his questions. One, what's the relationship with Amazon look like now? And the second question is, what should people know about Mongo if they haven't been keeping in touch with Mongo lately? What's the new, big bumper sticker that they should know about from Mongo? >> On the first point, the relationship with Amazon is very strong. We obviously partnered with them originally when we built Atlas and continued to do so. And just core architecture. Building a database and service that's best in class on their platform. And expanding initially from four or five regions to now global footprint and that was the first phase. Now, we're heavily focused on going to market. Whether it's our sales teams working together on accounts, working on migration opportunities, or new application architectures. Whether it's marketplace adoption that we're together, trying to drive in inquiries. There's quite a bit of collaboration happening. Certainly they have databases and services, but we believe certainly functionality-wise, there's a huge ecosystem around Mongo, and they see that and want to empower them with Atlas. So that's been a huge advantage to driving growth into the market. The second point around what I would want people to know about Mongo is, MongoDB today probably would surprise people from our original roots. Our original roots were systems of engagement, high scale web applications, new apps, we're fantastic at that. Obviously, Stitch is a way to double down on that value. But as I touched upon earlier, now we're really betting on a more general purpose strategy, where we brought forth things like transactions and acts of compliance for the first time to non-relational databases. So we really believe that there's no application today for which Mongo can't give the same level of developer benefit. Even if it's a heavy transactional mission-critical application. >> Doubling down on the web app, core business, giving them more range and functionality to go anywhere they want to go with those apps. >> Exactly. And, saying alright, there's this huge wave of billions of dollars built on legacy technology, how do we unlock those applications, get them on a modern platform, that allows those apps to stick around for the next 20 years and deliver customer values. >> It's not your dad's tingen, I guess that's the take away. >> Inside joke, tingen. Formerly MongoDB. Thanks for coming on The Cube. Great to see you. Congratulations on your role at Mongo. Great company, CMO. Great to see your success, thanks for coming on. >> Thanks for having me, I really enjoyed the conversation. >> The Cube, here live in New York City. More coverage, stay with us. I'm John Furrier with Jeff Frick. We'll be right back, thanks for watching, stay with us.

>> Narrator: Live from the Wynn Hotel in Las Vegas, it's theCUBE covering Magento Imagine 2018. Brought to you by Magento. >> Hey, welcome back to theCUBE. We are continuing our coverage live from the Wynn Las Vegas at Magento Imagine 2018. We've had a really exciting day talking about commerce and how it's limitless and changing dramatically. Joining me next is Sucharita Kodali, the vice president and principal analyst at Forrester. Sucharita, it's great to have you on theCUBE. >> Thanks for having me, Lisa. >> So commerce is limitless. We've been hearing this thematically all day. You primarily are working with retailers on their digital strategies. And you've been doing this for a long time. Let's talk about the evolution that you've seen in the retail space with everybody expecting to have access to whatever they want to buy in their pockets. >> Right, right, right. I would say, so I've been working in the retail industry for the last two decades. I've been an analyst for the last 10 plus years. I've really seen a number of changes. And if I had to just summarize the biggest changes, one is just the inventory across different retail channels. So, that's definitely been a huge huge one. It's like, how do you, how do you order online, but then fulfill the item from a physical store or fulfill the item from another store? So those are, that's basically the digital transformation of retailers. Those are investments that companies like WalMart and Target have really been doubling down on and focusing on. The second big change is Amazon. And they single-handedly have transformed the retail industry. They have increased consumer expectations. And what Amazon's also done is reinvented retail as a business model. Because it is no longer about just selling product and being profitable selling that product. Amazon actually is not profitable with a lot of the items that it sells. It makes money in other ways. And it is probably what I would describe as America's first retail conglomerate. And that becomes a really interesting question for other companies to compete, do you have to become a retail conglomerate? Then, the third big change is just brand selling direct to consumer. I remember when I started at Forrester, my very first project was with a large consumer electronics company that asked, Well, should we even sell directly to consumers? There's channel conflict and issues with our distributors. And now, that's not even a factor. It's sort of table stakes you have to sell direct to consumer. And that's probably where we'll continue to see a lot of retail sales in the future. >> So the Amazon model, we expect to be able to get whatever we want whenever we want it, have it shipped to us either at home or shipped to us so we can go pick it up at a store. It's really set the bar. In fact, they just announced the other day that a hundred million Amazon Prime members. I know people that won't buy something if it's not available through Prime. But I think this morning the gentleman that was on main stage from Amazon said at least 50% of their sales are not products they sell, they're through all of the other retailers that are using Amazon as a channel as part of their omni-channel strategy. If you think of a retailer from 20 years ago, how do they leverage your services and expertise and advice to become omni-channel? Because as today, you said essentially it's table stakes for companies to have to sell to consumers. >> Yeah, yeah. There are so many questions that really require, I call it destroying the retail orthodoxies. And retail has historically been about buyers and merchandisers buying goods. There's the old expression in retail, You stack 'em high and watch 'em fly. And that is just where buyers would, Take a company like Toys R Us, they would basically take what Mattel and Hasbro told them to buy. They would buy a ton of it, put it in stores. And because there was less competition back in the '80s, consumers actually would buy that merchandise. And unfortunately, the change for retailers is that consumers have so much more choice now. There's so such more innovation. There are small entrepreneurs who are creating fabulous products, consumer tastes have changed. And this old paradigm of Mattel and Hasbro, or kind of fill in the blank with whatever vendors and suppliers, pushing things is no longer relevant. So, there was just an article in the journal today about how Hasbro sales were down by double digits because Toys R Us is now going to go out of business. So those are the kinds of things that retailers who did not adjust to those changes, they are the ones that really suffer. They don't find ways to develop new inventory, they don't find new channels for growth, and they don't protect their own. They don't build a moat around their customers like Amazon has done, or they don't find ways to source inventory creatively. That's where the problems are. >> You think that's more of a function of a legacy organization; having so much technology that they don't know how to integrate it all together? What do you think are some of the forcing functions old orthodoxies that companies that don't do it well are missing? >> Yeah, it's a lot of it is just in the old ways of doing business. So, a lot of it is being heavily dependent, for instance, on buyers and merchandisers buying things. I mean, one of the biggest innovations that Amazon realized was that, look you can sell things without actually owning the inventory. And that is, their entire, what we call the third party marketplace, and that is just so simple. But if you were to ask a buyer at a major retailer a decade or two ago, "Why do you have to buy the inventory?" their response would be, Well, you have to buy the inventory, that's just the way it is. And it's like, well why? Why don't you try to find a new way to do business? And they never did. But it took Amazon to figure that out. And the great irony of why so many retailers continue to struggle is that Amazon has exposed the playbook on how to sell inventory without owning it. And so few retailers to this day have adopted that approach. And that's the great irony I think, is that that's the most profitable part of Amazon's business is that third party marketplace. And every retailer I've talked to is like, Oh, it's really hard. We can't do that. But, the part of Amazon's business that everyone is looking to imitate is their fast shipping. Which, is the most expensive part of their business. Amazon is only able to afford the fast free shipping because of the third party marketplace. Other retailers want to get the fast free shipping without the marketplace. And it just doesn't make any sense. And that's really the heart of the challenge is that they just don't think about alternative business models. They don't want to change the way that they've historically run their businesses. And some of this could mean that merchants are not as powerful in organizations. And maybe that's part of the pushback is that, there could be a lot of people who lose jobs. The future will be robo-buyers and financial services you have robo-advisors, why not robo-planners in retail? >> So one of the keys then, of eliminating some of the old orthodoxies for merchants is to be able to pivot and be flexible. But it has to start from where in an organization from a digital strategy perspective? Where do you help an organization not fall into the Toys R Us bucket? >> Yeah, I think a lot of it does have to start with merchandising and putting in some interesting digital tools to help merchants be more flexible. So, you want to flex to supply and demand. And some of that comes with integrating marketplaces into your own experience. Some of it can be investing in 3D printers that can make things that are plastic or metals based on demand. That's something that I always wondered why Toy R Us didn't, for instance, make Fidget Spinners on demand. Why did you have to get them with a six month leave time from China, it never made any sense. You can scale service, so use technology to match great store associates with a customer who may have a question. And you don't have to be in the same store. It can be a Facetime call with somebody who is far away. But very few retailers do that. And finally, the last bit is really to look at new alternative business models and finding new ways of making money beyond just selling inventory. >> That's really key because there are so many oppurtunities when companies go omni-channel of not just increasing sales and revenue, but also reducing attrition, making the buying process simple and seamless. Everybody wants one click, right? >> Right. >> Super seamless, super fast, and relevant. It's got to be something if you're going to attract my business, you need to be able to offer something where you know me to a degree. >> Absolutely. >> Or know what it is I might have a propensity to buy. >> Absolutely. And that's the entire area of personalization. And that personalization can be anything from a recommendation that I give you. It can be proactively pushing a recommendation. That's what companies like Stitch Fix do is I tell you what I want and then they send you a box in the mail of things I think you would like and oh, by the way are your size and within your budget. It can be customization. One of Nike's most successful parts of their business is their Nike ID program which allows you to customize shoes according to colors and different sort of embellishments that you may like. And that's exactly the kind of thing that more retailers need to be looking at. >> What are some of the trends maybe that a B2B organization might be able to love or some of the conveniences that we have as consumers and we expect in terms of-- Magento, I was looking on their website the other day and a study that they've done suggests 93 percent of B2B buyers want to be able to purchase online. So, new business models, new revenue streams, but it really is a major shift of sales in marketing to be able to deliver this high velocity low touch model. What are some of the things that a business like a Magento, could learn from say a Nike with how they have built this successful omni-channel experience? >> Well, interestingly I think one of the most important things to recognize is that every B2B buyer is also a B2C buyer. And their expectations are set by their experiences in B2C. So, if you have everything from all of the information at your fingertips, all of that information is optimized for mobile devices. You have different ways to view that information, you have all of your loaded costs, like shipping, or tax, or if there's cross-border. All of the information related to the time to ship, any customs and duties, all of that needs to be visible because in any experience that you have with say a site like Amazon, you're going to get that information. So, the expectation is absolutely there to have it in any situation whether it's B2B or whether it's buying components or kind of very long tail items. That's basically the cost of doing business at this point, is that you have to deliver all of the information that the customer wants and needs. And if you don't, the customer is just going to opt to go purchase that product at whatever destination offers it. >> Somewhere else. >> And somebody will. That's the challenge when you have 800 thousand Plus eCommerce sellers out there selling every product imaginable in the both B2B and B2C landscape. >> So, on the data side there's so much data out there that companies have any type of business to be able to take advantage of that. I know that there's, BI has so much potential. Are you hearing retailers start to embrace advanced analytics techniques, AI machine learning, Where are they with starting to do that? I know that some eyeglass companies have virtual reality augmented reality type of apps where you can kind of try on a pair of frames. Where are you seeing advanced analytics start to be successful and help retailers to be able to target buyers that might say, oh, I can't try that on? No, I want to go somewhere that I can touch and feel it. >> Yeah, well, it's emerging still. I mean, retailers have a lot of data. I think they're trying to figure out where is it most useful. And one of the places where it is incredibly useful is in the backend with fraud management. So, after retailers were forced to put in chip cards as a payment form, what you started to see was more of the fraud shifting to eCommerce. I just had two credit cards that had to be shut off because of E-commerce fraud. But that is where you see the fraudsters going to. And what you see as a result of that is some innovators in that space technology companies really leveraging machine learning, AI, other advanced data techniques to identify fraudulent transactions and to better help retailers eliminate or reduce the percent of transactions that have to then be charged back. So, that's probably one of the most promising areas. There are others that are emerging. We're seeing more visual recognition technologies. House for instance, is excellent at that and Pinterest too. If there's part of an image you like you can click on it or you can tap it and see other images like that. And that's incredibly difficult. And it was even more difficult 10-15 years ago, but it's becoming easier. There's the voice element, voice to text or text to voice. I think that the best applications they're often in customer service, there are so many interactions that happen anywhere in a consumer facing world. It doesn't even have to be within retail. You can think about the complaints to the airline industry or to a bank. And a lot of it falls into a black hole. You always hear that oh, This call may be recorded, but it is really difficult to go back and transcribe that. And to really synthesize that into major themes. And what ML in particular can do is to basically pull out those themes, it can automate all of that, and can give insights as to what you could be doing, what you should be doing, what are the opportunities that you may not have even known existed. So there are definitely emerging places. I mean even a visual recognition, so we talked about House and Pinterest. Another great example is the computer vision that you have in the Amazon Go stores. And there's a robot that the Wal Mart stores are now testing to go find if there are gaps in the inventory that need to be filled. Or if something is running low or out of stock. So there are definitely some interesting applications, but it's still early days for sure. >> So last question, we've got to wrap here, but, we're in April 2018, what are some of the, your top three recommendations for merchants, as they prepare for say Black Friday coming up in what, six or eight months. What are you top three recommendations for merchants to be successful and be able to facilitate a seamless online offline experience? >> Well, we always have kind of imbalances between supply and demand, and that's where I do think things like third party sellers, third party marketplaces are huge. So to be able to leverage that is certainly one opportunity. Another is to think creatively about promotions. In Japan they have these promotions called Fukubukuro promotions, and it's basically like grab bags of like all the left over inventory. But then they basically put it into mystery bags where you can buy it for half off. And consumers line up around the block at stores to go buy these grab bags. Because they also have also like a gamified approach where, you know, one of out 10 of the bags will have like an Ipad or some really high value item. So people really like these things, and they have trading parties. So just new ways of having promotions beyond just the typical door busters that retailers think about. And then kind of third I think is just try to pace out the demand. One of the big issues in E-commerce has been just the burst in demand that always happen in December. And that creates a lot of problems from the standpoint of actually shipping the orders. So the more that you can pull those transaction forward into November, the better off you are from a fulfillment and supply chain standpoint. >> Alright Sucharita thank you so much for stopping by theCUBE >> Thanks Lisa >> And sharing your insights on the trends and what's going on in the commerce and E-commerce space. Really enjoy talking with you. >> Nice to talk to you too. >> We want to thank you for watching. You're watching theCUBE live from Magento Imagine 2018, I'm Lisa Martin. Stick around, I'll be back with my next guest after a short break. (upbeat music)