>> Okay. We're here with Vasanth Kumar who's the Principal Solutions Architect for MongoDB. Vasanth, welcome to "theCube." >> Thanks Dave. >> Hey, listen, I feel like you were born to be an architect in technology. I mean, you've worked for big SIs, you've worked with many customers, you have experience in financial services and banking. Tell us, the audience, a little bit more about yourself, and what you're up to these days. >> Yeah. Hi, thanks for the for inviting me for this discussion. I'm based out of Bangalore, India, having around 18 years experience in IT industry, building enterprise products for different domains, verticals, finance built and enterprise banking applications, IOT platforms, digital experience solutions. Now being with MongoDB nearly two years, been working in a partner team as a principal solutions architect, especially working with ISBs to build the best practices of handling the data and embed the right database as part of their product. I also worked with technology partners to integrate the compatible technology compliance with MongoDB. And also worked with the private cloud providers to provide a database as a service. >> Got it. So, you know, I have to Vasanth, I think Mongo, you kind of nailed it. They were early on with the trends of managing unstructured data, making it really simple. There was always a developer appeal, which has lasted and then doing so with an architecture that scales out, and back in the early days when Mongo was founded, I remember those days, I mean, digital transformation, wasn't a thing, it wasn't a buzz word, but it just so happens that Mongo's approach, it dovetails very nicely with a digital business. So I wonder if you could talk about that, talk about the fit and how MongoDB thinks about accelerating digital transformation and why you're different from like a traditional RDBMS. >> Sure, exactly, yeah. You had a right understanding, let me elaborate it. So we all know that the customer expectation changes day by day, because of the business agility functionality changes, how they want to experience the applications, or in apps that changes okay. And obviously this yields to the agility of the information which transforms between the multiple systems or layers. And to achieve this, obviously the way of architecting or developing the product as completely a different shift, might be moving from the monolith to microservices or event-based architecture and so on. And obviously the database has to be opt for these environment to adopt these changes, to adopt the scale of load and the other thing. Okay. And also like we see that the common, the protocol for the information exchange is JSON, and something like you, you adopt it. The database adopts it natively to that is a perfect fit. Okay. So that's where the MongoDB fits perfectly for billing or transforming the modern applications, because it's a general purpose database which accepts the JSON as a payload and stores it in a BSON format. You don't need to be, suppose like to develop any particular application or to transfer an existing application, typically they see the what is the effort required and how much, what is the cost involved in it, and how quickly I can do that. That's main important thing without disturbing the functionality here where, since it is a multimodal database in a JSON format, you don't easily build an application. Okay? Don't need a lot of transformation in case of an RDBMS, you get the JSON payload, you transform into a tabular structure or a different format, and then probably you build an ORM layer and then map it and save it. There are lot of work involved in it. There are a lot of components need to be written in between. But in case of MongoDB, what they can do is you get the information from the multiple sources. And as is, you can put it in a DB based on where, or you can transform it based on the access patterns. And then you can store it quickly. >> Dave: Got it. And I tell Dave, because today you haven't context data, which has a selected set of information. Probably tomorrow the particular customer has more information to put it. So how do you capture that? In case of an RDBMS, you need to change the schema. Once you scheme change the schema, your application breaks down. But here it magically adopts it. Like you pass the extra information, it's open for extension. It adopts it easily. You don't need to redeploy or change the schema or do something like that. >> Right. That's the genius of Mongo. And then of course, you know, in the early days people say, oh, you know, Mongo, it won't scale. And then of course we, through the cloud. And I follow very closely Atlas. I look at the numbers every quarter. I mean, overall cloud adoption is increasing like crazy, you know, our Wiki Bon analyst team. We got the big four cloud vendors just in IAS growing beyond a 115 billion this year. That's 35% on top of, you know, 80-90 billion last year. So talk more about how MongoDB fits with the cloud and how it helps with the whole migration story. 'Cause you're killing it in that space. >> Yeah. Sure. Just to add one more point on the previous question. So for continuously, for past four to five years, we have been the number one in the wanted database. >> Dave: Right Okay. That that's how like the popularity is getting done. That's how the adoption has happened. >> Dave: Right. >> I'm coming back to your question- >> Yeah let's talk about the cloud and database as a service, you guys actually have packaged that very nicely I have to say. >> Yeah. So we have spent lot of effort and time in developing Atlas, our managed database as a service, which typically gives the customer the way of just concentrating on their application rather than maintaining and managing the whole set of database or how to scale infrastructure. All those things on work is taken care. You don't need to be an expert of DB, like when you are using an Atlas. So we provide the managed database in three major cloud providers, AWS, GCP, and Azure, and also it's a purely a multicloud, you know, like you can have a primary in AWS and you have the replicated nodes in GCP or Azure. It's a purely multicloud. So that like, you don't have a cloud blocking. You feel that, okay, your business is, I mean, if this is the right for your business you are choosing the model, you think that I need to move to GCP. You don't need to bother, you easily migrate this to GCP. Okay. No vendor lock in, no cloud lock in this particular- >> So Vasanth, maybe you could talk a little bit more about Atlas and some of the differentiable features and things that you can do with Atlas that maybe people don't know about. >> Yeah, sure Dave like, Atlas is not just a manage database as a service, you know, like it's a complete data platform and it provides many features. Like for example, you build an application and probably down the line of three years, the data which you captured three years back might be an old data. Like how do you do it? Like there's no need for you to manually purge or do thing. Like we do have an online archival where you configure the data. So that like the data, which is older than two years, just purge it. So automatically this is taken care. So that like you have hot data kept in Atlas cluster and the cold data moved up to an ARKit. And also like we have a data lake where you can run a federated queries . For example, you've done an archival, but what if people want to access the data? So with data lake, what it can do is, on a single connection, you can fire a- you can run a federated queries both on the active and the archival data. That's the beauty, like you archive the data, but still you can able to query it. And we do also have a charts where like, you can build in visualization on top of the data, what you have captured. You can build in graphs or you can build in graphs and also embed these graphs as part of your application, or you can collaborate to the customers, to the CXOs and other theme. >> Dave: Got it. >> It's a complete data platform. >> Okay. Well, speaking of data platform, let's talk about Io-Tahoe's data RPA platform, and coupling that with Mongo DB. So maybe you could help us understand how you're helping with process automation, which is a very hot topic and just this whole notion of a modern application development. >> Sure. See, the process automation is more with respect to the data and how you manage this data and what to derive and build a business process on top of it. I see there are two parts into it. Like one is the source of data. How do you identify, how do you discover the data? How do you enrich the context or transform it, give a business context to it. And then you build a business rules or act on it, and then you store the data or you derive the insights or enrich it and store it into DB. The first part is completely taken by Io-Tahoe, where you can tag the data for the multiple data sources. For example, if we take an customer 360 view, you can grab the data from multiple data sources using Io-Tahoe and you discover this data, you can tag it, you can label it and you build a view of the complete customer context, and use a realm web book and then the data is ingested back to Mongo. So that's all like more sort of like server-less fashion. You can build this particular customer 360 view for example. And just to talk about the realm I spoke, right? The realm web book, realm is a backend APA that you can create on top of the data on Mongo cluster, which is available in addclass. Okay. Then once you run, the APS are ready. Data as a service, you build it as a data as a service, and you fully secure APIs, which are available. These APS can be integrated within a mobile app or an web application to build in a built in modern application. But what left out is like, just build a UI artifacts and integrate these APIs. >> Yeah, I mean we live in this API economy companies. People throw that out as sort of a buzz phrase, but Mongo lives that. I mean, that's why developers really like the Mongo. So what's your take on DevOps? Maybe you could talk a little bit about, you know, your perspective there, how you help Devs and data engineers build faster pipelines. >> Yeah, sure. Like, okay, this is the most favorite topic. Like, no, and it's a buzzword along, like all the DevOps moving out from the traditional deployment, what I learned online. So like we do support like the deployment automation in multiple ways okay, and also provide the diagnostic under the hood. We have two options in Mongo DB. One is an enterprise option, which is more on the on-prem's version. And Atlas is more with respect to the cloud one manage database service. Okay. In case of an enterprise advanced, like we do have an Ops manager and the Kubernetes operator, like a Ops manager will manage all sort of deployment automation. Upgrades, provides your diagnostics, both with respect to the hardwares, and also with respect to the MongoDB gives you a profiling, slow running queries and what you can get a context of what's working on the data using that. I'm using an enterprise operator. You can integrate with existing Kubernetes cluster, either in a different namespace on an existing namespace. And orchestrate the deployment. And in case of Atlas, we do have an Atlas-Kubernetes operator, which helps you to integrate your Kubernetes operator. And you don't need to leave your Kubernetes. And also we have worked with the cloud providers. For example, we have we haven't cloud formation templates where you can just in one click, you can just roll out an Atlas cluster with a complete platform. So that's one, like we are continuously working, evolving on the DevOps site to roll out the might be a helm chart, or we do have an operator, which has a standard (indistinct) for different types of deployments. >> You know, some really important themes here. Obviously, anytime you talk about Mongo, simplicity comes in, automation, you know, that big, big push that Io-Tahoe was making. What you said about data context was interesting because a lot of data systems, organizations, they lack context and context is very important. So auto classification and things like that. And the other thing you said about federated queries I think fits very well into the trend toward decentralized data architecture. So very important there. And of course, hybridisity. I call it hybridisity. On-prem, cloud, abstracting that complexity away and allowing people to really focus on their digital transformations. I tell ya, Vasanth, it's great stuff. It's always a pleasure chatting with Io-Tahoe partners, and really getting into the tech with folks like yourself. So thanks so much for coming on theCube. >> Thanks. Thanks, Dave. Thanks for having a nice discussion with you. >> Okay. Stay right there. We've got one more quick session that you don't want to miss.