 Hi from San Francisco, it's The Cube. Hey welcome back, this is Jeff Frick. We're on the ground at the western St. Francis in San Francisco, California at the Cassandra Summit 2014. I'm joined by my next guest, Anand Venugopal, did I get it right? That's right, Venugopal. Venugopal. Great, thanks for stopping by. Thank you, nice to be here. Yeah, so you're from Ipitas, you're a system integrator, so we have a little different perspective. We've been talking mainly to customers and folks from DataStack. So, why are you here? What are you excited about? Well, we've probably been in every Cassandra Summit there ever was. Oh, so you backed like five Cassandra summits ago? Pretty much, yeah. Like 12 people. Yeah, so we've been working with DataStacks right from when they were Reptano, from when Matt and Jonathan began the company. And we actually started implementing Cassandra in large enterprises before DataStacks was even formed. So that's how long we go back with our Cassandra and DataStacks experience. And we are working with large enterprises on the east coast, on the west coast, many big global names in implementing their solutions on DataStacks Enterprise. So, talk a little bit about how the change in the enterprise environment, you know, five years ago, you know, how are things growing that you are going to take a risk with your company to implement in an enterprise who usually aren't too fond of start-up-y stuff, this new database. I mean, what was happening then and how does that continue to evolve over the last couple of years? So it was definitely a novelty and something that people were cautious about, something that people only were working with on an R&D and experimentation mode, right? When they started seeing the benefits, like hard core economic benefits of, you know, replacing hundreds of RDBMS licenses with Cassandra, people started really looking at this very seriously. And Cassandra's performance is obviously amazing. And that's what our customers care about. And the open source revolution is here and it's here to stay. People are really getting comfortable with it. And DataStacks Enterprise, of course, packages all the open source technology with enterprise-grade, you know, functionality and features around it, which customers want. And we're seeing that in a product that we are doing as well. We have launched a product called Stream Analytics, which is a streaming analytics platform that has out-of-the-box support for Cassandra, given that it's, you know, ingesting high-speed, high-volume data. You need a database that can take that kind of speed in terms of ride speed. And Cassandra is a great candidate for that. And we're soon going to be probably a full DataStacks Enterprise compliant in the roadmap coming up soon. So as much as you can share, I wonder if you can tell some of the customer examples, some of the use cases that you're seeing. Early days that they would motivate it to take that risk, but also kind of more recently now that people are more comfortable with open source and obviously the big data revolution and what's happening. What are some of the things that people are doing out there that are innovative, interesting, creative, fun? What do you like to talk about? Yeah, sure. We started long ago with Pitney Bose, actually. There was a petabyte-scale cloud-based implementation for putting your U.S.P.S. mails on the cloud, in a secure cloud environment. And they needed a database that scales out. It's good for the cloud, et cetera. And at that point on, we recommended Cassandra and became part of their blueprint. After that, we've done a number of implementations. You see pictures of Drew Johnson, one of our customers in ARIS communications. And they had an Oracle database. They wanted their real-time analytics kind of company where the machine data flowing through. And there's a lot of things they could not do with Oracle. They can with Cassandra. And in terms of scale out and in terms of fast ingest and building and real-time analytics, it's just a great candidate for that. And there's a lot of interesting use cases with that company where your 16-year-old is driving a Hyundai car and she's traveling out of the perimeter and you get an alert in real-time. And all of those events need to be recorded as they happen. And that's a bunch of interesting use cases, just that one company. And we're working with the large healthcare and legal services company in the East Coast, I can't mention the name. But they are doing trademark search at hundreds of thousands of scale and rapid, rapid response. And we're implementing Cassandra DataStacks Enterprise with the DataStacks East Coast team there. So talk a little bit about the impact of real-time in business. So what real-time really means to some of the customers that you're working on? So real-time streaming analytics adds business value on three dimensions. One is that it helps to cut preventable losses. So there are things like outages and maintenance breakdowns that can be easily predicted and prevented by analyzing the real-time data and predicting that event coming in. That's real-time analytics. Operational intelligence like security and data from various devices and doing quality and management monitoring. That's a real-time use case right there. Customers coming on your website and interacting with your website and getting real-time contextual feedback on the next product that they need to purchase is real-time analytics in the ad world. So there's a lot of business value and opportunities in the real-time streaming analytics space. There's a webinar that we've actually conducted and recorded on our website, impetus.com. People can go check that out. And our business is figuring it out. Are they coming up to speed now where it's not, get the data, analyze the data, make a decision? But now it's, you're collecting the data constantly. It's this constant data flow. Being able to really make sense of that data, convert the data and information, the information, the insight, the insight to action, as the pyramid is often described. What's the adoption? What's the uptake? Where's that being driven in some of the organizations you're working with? Believe it or not, the open source revolution has caught up in a great way where the biggest companies in the world are leading the charge in technology implementation. So they've done with their batch analytics implementation. And they're all looking to move to add real-time data feeds into their infrastructure. So they're adding that whole silo on their enterprise data architecture where they need a fast and just database like Cassandra and search. So data stacks enterprise is just a perfect solution there. And they're augmenting their batch infrastructure with a real-time pipeline so that they can actually feed data, analyze it as it comes, transform it as it comes before getting into the database so that it's ready for analytics and they can immediately take advantage of that. And the other thing they're doing is blending real-time data with historical data to give the full context. So if you call into a telco, the operator, the person who's serving you really gets the full feed of who you are, what you did in the last six months, every event. And they're able to serve you much better. And how much of that is the technology catching up to the demands of the business? Or is it now the technology guys say, hey, we can do this, we can do this, we can do this, and now the business is getting an opportunity to rethink the way that they collect data and make decisions? The business is discovering that they can do a lot of cool things. And they didn't know that they could do it. And some of them ask for it, but some of them are being told by the technologists, hey, this is possible. So there are some IT departments that are proactive, that are putting in the infrastructure. They know that this is coming. The business is not pushing for it yet. But even large telco, I was just in New York last week, a major cable company is already implementing real-time streaming analytics part of the infrastructure. The guy knows the business is going to ask for this in two months. I know that, there's plenty of use cases. So it's both, both patterns are being clearly played out. The business is driving as well as technologies are putting proactive infrastructure in place. That's great. So I'll give you the final word. You've been coming to these since the beginning. What's kind of your thoughts, your feelings here as you come into Cassandra Summit 2014 relative to where it's been? The reality of it and the expanding scale is just overwhelming. It's overwhelming. It's just exciting to see enterprises at all levels uptake this technology and really make it real. So big data and Cassandra and data stacks is here to stay. And I'm really looking forward to the whole growth path, even going forward. Awesome. Well, no, thanks. Thanks. That's a great wrap. So again, Jeff Frick here on the ground at Cassandra Summit 2014 at the Western St. Francis in San Francisco, California.