[00:04]Bill Peterson: Hi, I'm Bill Peterson VP, Industry Solutions with MapR. This is Mitesh Shah, director of product marketing with MapR. We're going to talk about our recently announced MapR Clarity Program.
What is the MapR Clarity Program and what do customers get out of it?
So Mitesh, what is the MapR Clarity Program and what do customers get out of it?
[00:19]Mitesh Shah: Well the MapR Clarity Program is a program meant to solve customers' biggest and most pressing data challenges today. So the program itself actually consists of three key parts. Part 1 is the data platform itself, the MapR Data Platform. And that data platform really solves the key challenges in the world of data for all of our customers today around themes like AI and ML, around Hybrid and Multi-Cloud.
Around Containers – Specifically Stateful Containerized Applications and Operational Analytics. So that data platform is available today and that's really part one of the program. Part two of the program is what we're calling StepUp to MapR. And what this is, is a professional services offering its free data assessment that entails our professional services team coming out to your organization and they will conduct a one-week long engagement where they will identify your business goals, your requirements, your use cases, even what data sources you might have.
And come up with an implementation plan for getting to the MapR Data Platform and solving your business needs around data. So obviously we have many customers that are using MapR today and this data assessment really removes a risk, any risk associated with moving to MapR and this is really for any customer or prospect today wherever you are on your journey.
It could be you have legacy systems and you're thinking about moving to a more production ready data platform, you could be a Cloudera or Hortonworks customer and we welcome you as well into that program too. So that's really part two, is the data assessment.
Part three of the program is a free, on-demand, training. So some of these concepts are obviously quite confusing around Kubernetes, AI, ML. What are you supposed to do with all this? From a business perspective, we actually offer essential courses around these technologies so you can get acquainted with them, and what you might be able to do with them.
We also offer more technical deep dive courses into things like; Spark, and SQL Analytics, and even around the MapR Data Platform itself so you can ultimately get certified in these technologies. So again, these are free training courses that you can take advantage of today. The three parts of the program are the; data platform, the free data assessment from our professional services team, and the on-demand training.
What's the goal here? And what are the benefits? And why would a customer do this?
[02:50]Bill Peterson: Great. So let's be a little more specific. What's the goal here? And what are the benefits? And why would a customer do this?
Mitesh Shah: That's a good question. So what is the goal here, right? We've seen actually two points of confusion in the market today. One point of confusion really is around how you can start solving for these business challenges around the technologies that I just mentioned. And things like; how do you take advantage of ML and AI? And do it potentially on the same cluster as your analytics?
You want to evolve from analytics to AI and ML, but you're not able to do that with existing technologies. Same story for Hybrid Multi-Cloud. You want to deploy Multi-Cloud applications but there's really no great way to do that. With Legacy Technologies or our competitors for that matter, as well as solving for Stateful Containerized Applications and Operational Analytics. So there are all these pain points that the customers and organizations really want to solve for but can't do it with alternative technologies.
So that's one piece of it. The other piece is really around the merger which most of you probably heard of at this point. The merger between Cloudera and Hortonworks that was announced in early October and all the confusion that is going to ensue as a result of that merger. So really two pieces to that first, these technologies from Cloudera and Hortonworks in particular, are built on what I call shaky foundation.
They're not built on a sound architecture and as a result, their customers and prospects by and large are suffering. They're not able to go to production and they're certainly not able to meet the needs around all the themes that I just mentioned. AI, ML, and so forth. So that's the one piece of it and the other piece of it is the redundant aspects of all the projects that these organizations have. In the world of security, Cloudera has Sentry, Hortonworks has Ranger, in the world of governance. Cloudera has Navigator, and Hortonworks has Atlas.
So these are all duplicate redundant offerings that ultimately, over time, will need to get rationalized as these organizations do their cost-cutting. Which, arguably, is the point of the merger in the first place. At least according to the analyst reports and the SEC filings that I've seen. So there's a lot of confusion there, so again those two things are really colliding, creating this perfect storm of confusion for customers and the MapR Clarity Programs aims to cut through all that and provide the clear path forward to solve for customers and organizations production needs.
Do you have an example of a customer who stepped up to use MapR?
[05:15]Bill Peterson: Got it. So let's provide some context for our viewers. Do you have an example of a customer who stepped up to use MapR?
Mitesh Shah: No, I've got many examples. Many over the years have, what I call, graduated, from Cloudera and Hortonworks over MapR. Starting with really several years ago, five, six, seven years ago we had Comscore that has moved their big data analytics platform over from Cloudera to MapR.
Now the reasons for that ... there are probably several reasons for that, but one big reason for that is MapR support for NFS. NFS is a big differentiator for us in the world of big data. So this really allowed them to connect their existing legacy and enterprise systems into MapR.
And so it's a big reason for them to move to MapR and there have been many other customers along this road a well, including some that really just didn't like the name Node Architecture and all the bottlenecks that the name Node Architecture run into with Cloudera and Hortonworks. Right? So MapR has no name node architecture, our metadata is distributed across our data nodes and as a result we are able to scale more, and simply have higher availability.
So customers have moved off from these competing platforms over to MapR for that reason and then most recently Cequint, a provider of caller ID services out of Seattle, has chosen to move to MapR from a competing offering because they couldn't deal with all the problems with data ingestion, resulting from the sub-par underlying architecture and chose MapR, really again because of our support for NFS.
And we're able to do that because we've got a read/write file systems and our competitors have an append-only on file with HDFS and that really has downstream implications for a lot of things so lots of customers over the years.
[07:14]Bill Peterson: Great, thank you. Lots of great information there on our Clarity Program. Join us next time when Mitesh will clue us in to some of the security benefits of the MapR Clarity Program. Thank you.