 And welcome back, we're here live at Strata Conference and Hanoop World in New York City. I'm Jeff Kelly with wikibon.org. We're here live inside theCUBE, SiliconANGLE's premier TV production. We're here with two great guests from Datastax, Lara Shackleford, VP of Marketing, Rahman Shoemaker, VP of Products. Welcome to theCUBE. Great to have you guys on. So we just heard from Venky from Thompson Reuters, a Datastax customer. And what really struck me was the, kind of the complimentary nature of the Cassandra and the Hadoop platform that you guys provide him. Tell me a little bit about, we heard about some of the ways he's using Cassandra and your product. What are some of the trends you're seeing? Is Venky kind of representative of some of the trends you're seeing? Yeah, absolutely. The thing is, the whole big data idea is, for one of a better term, extremely legit. The idea of high velocity data coming in, variety of data, volume of data, and then really the complexity of data is very real with all of our customers. And so whether it's Venky with Thompson Reuters, whether it's in the media area, whether it's in healthcare, all of these things are occurring. So for example, we have one of our customers, healthcare anytime. These guys, we're trying to use legacy traditional relational databases, hit the wall very quickly, couldn't add more than 10,000 patients an hour to their online health portal. They needed something else. And so by necessity, they came to a NoSQL database, they came to Cassandra to be able to ingest all of that information, consume all the information. That got them past that particular issue. Once they had all that information, then they can very easily move that over into the analytics Hadoop nodes for analysis on things like doctor notes that help them build Medicaid. And then all that information is also available for enterprise search, which we also provide. So they can do things like very quick online searches for a doctor who speaks German, who's five miles close to my home, things like that. So the entire platform of DataStacks Enterprise provides them with all the ability to really take on that whole big data challenge. So one of the things we hear, we're here at Hadoop World, but people sometimes think Hadoop, they think, well, that is big data, but there's more than just Hadoop as we're seeing. So it's interesting, how do you guys define big data? I mean, what does it mean to you in terms of is it a technology or is it more of a mindset? Because the way we're looking at it and some of the research we're doing, it seems like it's more than a technology. It's a way of thinking about data and a way of thinking about how you're going to monetize that data and make use of it. What's your take on the bigger picture definition? Yeah, I think you're right. I think the technologies are definitely underpinning the ability to now utilize something that perhaps people couldn't do anymore. They always wanted to, but they never could. So for example, one of our customers, Constant Contact, same thing, they could only keep 90 days of data online to be able to service all of their marketing customers that they take care of. They had all the social media information coming in, they wanted to do more, but their DB2 database just couldn't handle it. So now they came to Cassandra, lo and behold, now they can store years worth of data versus just 90 days. And so what we see are a blend of those traits that I mentioned earlier, maybe not all of them. The ones that we see the most, high velocity data coming in, being able to very quickly ingest that data, variety of data, structured, unstructured, semi-structured, and then the complexity of data is especially true, having to take that data into multiple geographies, multiple data centers, and be able to have true location independence, being able to read and write anywhere and bring all that together. And then finally the volume comes in afterwards, but most of the time it's velocity, variety, and complexity with volume coming in after that. So, sorry, go ahead. I would add to that. We power apps for customers that are transformational for their business. So we tend to find, in the example of healthcare anytime, we had a customer who wanted to transform their experience for not just their customers who were largely hospitals, focusing on patients who subscribed to Medicare and Medicaid, but also their end users, and really creating a better experience for their end users. We get involved very much in understanding what our customer needs are and how we can help transform their organization. So whether it's someone like a healthcare anytime, a very well-known story for us is Netflix, who really worked with us to transform their experience for their customers, their end users who want to interact with Netflix in real time. And that's, again, high velocity of data, but very much to transformational in the way that it powers their business. Yeah, I can speak to that. I'm a Netflix user myself, so I've benefited from the technology that you guys are helping them extend to the consumer space, but you mentioned helping your customers transform. So, and you mentioned earlier, and we saw with Vinky hitting a wall with some of the traditional data management tools and technologies, but at the same time, they're not necessarily going away anytime soon, so it's a transition period. How do you help your customers manage that transition because it's not a matter of just ripping out your relational database? You kind of have to look at it, I think, kind of as a portfolio manager and find the least risky way to make that transition and to mitigate your risk where you can and maximize the value of these new types of technologies where you can. Absolutely. Yeah, we very much see a coexistence strategy happening in many of these cases where perhaps legacy relational databases are retained for what they're good for, asset-compliant transactions and that type of work, or managing perhaps small amounts of data that don't take on big data characteristics. So you'll still see an Oracle or a MySQL in play, but then when you have these apps that either start out or they really transform to become a big data application, out of necessity, that's when they have to turn to another SQL solution like Cassandra and then also an analytics solution that provides them that bulk and batch capability on that big data like Hadoop. So, Lara, in terms of the marketing message we were talking earlier about how kind of the CMO is quickly rivaling the CIO internal technology spend. So how does that impact from a marketing perspective talking to potential customers? Are you talking more to the business about business use case and value and less to IT or what's that balance like and is it shifting? I would say both. We're definitely, one thing we've found as a marketer, you have to talk to the right audience with the right message, but the spend is shifting and you definitely have to, we talked to Vinky earlier who has, from Thompson Reuters, who is a role in global development, we're speaking with this counterpart in the business this afternoon with Vinky and we have to make sure that they both understand and can perceive the value that we can provide them both on the technical level and on the business level. So one thing that we are doing more and more of is making sure that we address that business problem so it's not just about the technical aspects of what we can do but also about how we can bring that value to the customer and again, we're really focused on helping our customers and understanding where, helping them understand what that transition you were asking about is where we can help them now, where they can wait and use a traditional 35 year old system that has been working for them in other areas and we do that both on the business and the technical side. And you know, at the end of the day, really, for whatever business, it's all about two things, making money and saving money, okay? They want to make money by being able to use all the information, all the data that's coming in to make those business decisions in a very timely fashion and therefore help their company make money and at the same time, they've got to look at cost and one of the great things about data sex enterprise and what we do here is we can literally provide them with the types of technology that solve these issues at about a tenth the cost they're going to pay for these older relational systems. So, you know, one of the themes we're seeing here at this show is the kind of the real-time SQL-like capabilities coming into the Hadoop world. Clutter had an announcement in MapR, companies like HADAPT doing some interesting things there. You know, but that's, you guys take a different approach to that same business problem. Kind of compare and contrast how you approach that. You know, you've been doing it for a while. I mean, today we're just seeing some announcements. So kind of put it in context, kind of where you sit relative to some of these announcements that we're seeing today and really, why is it so important to have those two capabilities? Sure. So with Cassandra, what you basically have is a modern day transactional system of record system. So people like Vinkey and others, what they're looking to do is try to take their online business application and scale that. So that's a little different than what you have with a Hadoop or an analytics or a BI structure, type of infrastructure. So we have Cassandra that's being able to take in all this information and provide, again, system of record capabilities at scale, linear scale, being able to predictably and linearly scale your application. And then with the Hadoop side, being able to have, again, something that's a little bit better than they've had maybe in the past. With Hive, okay, you have the SQL access, but let's face it, it's still MapReduce under the covers and you're still having to wait. So now being able to have this real-time access for that analytic data, I think is a tremendous win for people. So, you know, I'd love to get your impressions of the show. I mean, we've seen that, you know, there's a lot of folks here doing some really interesting things. What are some of the things that you're most interested to kind of learn here? Are you here to talk to potential customers? Are you here to learn about kind of the, there's so many different areas of the big data space, the visualizations, doing some really interesting things, companies like Tableau. So what are some of the things that are kind of getting you excited this week? I'll tell you, Anna, you know, we're certainly here to learn and connect with our customers who are here. At the same time, we're really here to help to, there's so much hype around big data and we want to help to bring some, I guess, reality to that story, which is that is it about big data or is it about the value that we can bring to our customers? And we think it's about value and that's what it's always been about. So that's where we're focused and that's one of the reasons we wanted to be here, telling the kind of reality-based story. I think this year's show, I was at last year's Stratashow in New York and I've been to the ones in California. Always been a fan of the Stratashoes. I think this year's show is a very market improvement where we saw last year in terms of the New York excellent sessions and we're certainly here to learn about some of the new technologies because, Jeff, as you know, I mean, Datastacks Enterprise, we bring together a lot of the best of breed technologies into one big data platform, Cassandra, Hadoop, Solar and so we're always on the lookout for other technologies that are able to complement that platform and help our customers be able to manage all those various data domains again in one cluster. Yeah, I mean, I think that's really one of the direction we're going. It's kind of that having that one comprehensive platform rather than kind of that world of connectors, but as to the point we were talking about earlier, that transition from the old to the new takes time and it's not going to happen overnight and I think a key role that vendors like yourselves play are helping your customers understand that and actually navigate that. So we are out of time and thanks so much for coming on. Appreciate it very much. Datastacks, definitely check them out and thanks again for your support. Thank you for helping bring us the cube to Strato and Hadoop World. So thanks again, appreciate it. We'll be right back here live in New York City just after this. Thank you.