 Live from Las Vegas, Nevada, it's theCUBE at HP Discover 2014. Brought to you by HP. Welcome back to Las Vegas, everybody. This is Dave Vellante. Jeff Frick is back with me. This is theCUBE, SiliconANGLE's live production of HP Discover. theCUBE is a live mobile studio. We go out to events. We extract the signal from the noise at these conferences. We report to you, really appreciate your feedback. Go to crowdchat.net slash HP Discover. We're running a live crowd chat, which was announced today. Actually, you saw an article on Recode about crowd chat, so we're really excited about that. But if you've got questions, you can tweet them there or tweet me at at Dave Vellante and you are at Jeff Frick, right? Yep, yep. Okay, Paul Miller is here. He's the vice president of marketing for HP Converged Systems. We had Tom Joyce on yesterday talking about the trends in Converged. We talked about sharks. Paul's going to talk a lot about what went on last month, I guess. Last month? Last week. Last week. Last week in Sapphire. Sapphire's usually in May, right? It's in June this year. Well Paul, welcome back to theCUBE. Good to see you again. Good to see you again. So, give us the update. How was Sapphire? This is the first year I didn't make it in, gosh, it goes and how many? But what was it like this year? A lot of business being done at Sapphire. Yeah, no, Sapphire was great. Last week in Orlando, big buzz is still around HANA and what's going on, moving SAP landscapes onto the next generation in-memory technology based on HANA. And we had a really big announcement there on stage with Hasso and Bert Lucur, who took over for Vishal Sikha. Big announcement of our Converged Systems 900 platform, which is really the biggest, baddest in-memory database in the marketplace. The biggest, baddest. The biggest and baddest. Well, in memory just sounds big and bad. Yeah. Yeah. So, I want to ask you, what do you make of Vishal Sikha? Sort of surprise news, him moving on, but what do you make of that? Yeah, every organization goes through evolutions, right? Bert is from the business application side. So he's going to bring, I think, that expertise of sweet on HANA that was his product. That is the holy grail, right? Because if you look at big data, right, there are really two different use cases. One is for systems of record, right? Transactions, credit card transactions, those things that are very, very important. That's where in-memory plays. The others are systems engagement, right? The systems of engagement are where Hadoop and Vertica play, where you go and get the customer engagement, the customer insight. In the past, those two have been two separate systems, right? You collect your data and do your transactions in one database and then you ETL it. You move it to another sandbox to do the analysis of it and to get the insight. With this announcement of the CS900 versus 900 and HANA, now you bring those together. Or first time you have a database scaling up to 12 physical terabytes of data where you can do the in-memory transactions and analyze it at the same time. This is revolutionary, right? So when people talk about big data and in-memory, they usually focus on the speed. But there are two important other elements that are really bigger than just the speed. It's the ability to have this transformational, business transformation of doing real-time analytics on the data and not moving it out. And what that does then is bring massive simplicity. Customers I talk to, they spend more time moving data from the transactional database into another database for BW or analytics. That takes time, resources, adds complexity, multiple different tools, software. Now when you can collapse that all into one, you have a great solution that is highly scalable, simplicity, taking out more simplicity than you can out of anything else. And that's the real magic of what we announced with the Convert Systems 900. Yeah, we talked a lot about the potential to bring together transactional data and analytic data operating on it in real-time or near real-time. Essentially we define real-time as before you lose the customer. So what kind of workloads are you seeing? Obviously, ad serving is one. What other type of workloads are you seeing? So we're seeing customers move their ERP information into there, their customer information. Yeah, for really trying to make those decisions in real-time, to be able to understand what's happening with your supply chain. You can drill down into a country. What's happening with that product? And understand, why is it not selling? Is it a big problem? Or is it a smaller problem? With the new technology, you know, we look at things in aggregates, right? You start on an aggregate, you look at a product line, a country, right? And then typically in a system where you move that data off into another database, you may only get three clicks down and say, okay, I understand the product line has problems, I understand it's in Latin America. But then you have to go extract data again to go double-click on that. And it may only be in a specific country. So you aggregate the data so many times, you start to lose control of your ability to query. When you move it all together and be able to query on it in real-time in the exact database, you move the aggregates and you can query all the way down to maybe a specific country, even a specific store. And that's what's the power of this, what we're talking about, big data. So this notion of in-memory and in-memory databases been around since we've had memory. Why now is it so hot, is it taking off again? One is it's the cost of memory has come down significantly. Two, architectures like the CS900 enable you to scale to 12 terabytes. Most customers can get C compression from three to up to 10%. So we talk about real-life data of OLTP data in the 50 to 80 terabytes. That means now that almost any workload in the world, any database in the world, we can handle and drive. So in the past when you can only have scalability to two or four terabytes, not that interesting for most people's real-time data, most retailers, big financial shops, but now with 12 terabytes, you can really get the performance and the scale that you need. Okay. It's because they talk about the business impact of not having to aggregate so much. This is a very, very different shift when we see the funny commercials on TV about the market of one, but in the real world and in the customers you're talking about, how is that really impacting the way that they make decisions and the way that they're looking at their business? Right, so by getting away from looking at just the aggregates, right, and you can think about it, right, we're all customers, right, and you can do a customer profile looking at multiple different attributes. But in the end, what you have to sell to is the task that a person is doing. And by distributing the aggregates and getting rid of those aggregates and focusing on that, Jeff, you have a task in the morning. You want to know what's happening in the world. We don't care from all the aggregates how many kids you have, whether you're married, we care about that you need to learn the news. And that's what you can do now by distributing the aggregates and getting down to the facts. Hopefully that makes sense, but it's kind of complicated theories, but that's what in memory allows you to do. Yeah, well the one that always intrigues me is the insurance business. And I'm really curious to see how the insurance business evolves in the age of big data, because clearly insurance is based on an aggregation of risk. We all pool our money in, we all pool our risk, and for the poor and fortunate soul that something bad happens to, there's a pool of money. Well, you've seen a slowly and a little, tiny slices of drilling down sex, weight, age, a few things, but now in this age, when you can get so much more data for the individual, how does that impact a business model based on aggregation? I'm still confused. Well, I think it's going to impact the insurance, whether it be health insurance, and your driving ability to collect data points, not on that Jeff, you're a middle-aged man just like me, and your insurance is based on that, but actually how you drive, you will collect those data points. So that's really critical. So insurance from those capabilities to banking in loans, it's going to revolutionize and give customers more information to make better decisions, higher profitability, lower risk for their businesses. So I'm going to have to ask you, where does flash fit into this whole thing? So it's great, it sounds good, do everything in memory, but at some point I got to persist this stuff. Right? Preserve what I want to save it. And so how do I persist the data? So if you look at our architecture with the CS900, we use a mix of hard drives, in memory, flash and hard drives to optimize. So you put your logs off really fast to flash so that you can always rebuild your system. So you'll see this balance over time, and then that'll go away when technology's like memories to come to marketplace. When you truly have true scalable persistent memory, then things like going out to flash. All right, when's that? When's that? Give us a take. You'll have to talk to Martin and thank him about theCUBE here. It's coming in the future. He'll be talking about it in the keynote later today, but that's the holy grail, and that's when I think the whole explosion and people's mindset on what's happening within memory and highly scalable architectures is going to really explode and have so many new use cases, like you say with insurance, et cetera. That's the next big milestone in this. So customers today can really achieve the speed, some of this business transformation, but not the full simplicity until we get to Memrister and that persistent memory. Let's talk about the competitive dynamic because every company out there, I guess with the exception of IBM and Oracle, are hopping on SAP HANA. They see it as a way to build a partnership with SAP, a very important application, ISV. Why HP? Why will customers gravitate toward HP versus some of the other guys that are pushing, whether it's converged infrastructure or other products? Right, so if you look at the average customer, HP, we don't have one SAP instance. We have multiple SAP instances. 30 plus SAP instances, I can't tell you the number, but it's a big number. Every customer I go to, major manufacturers, you find hundreds of SAP instances. And so it's not a one-size-fits-all. They want an architecture that can scale and consolidate and simplify down to one architecture. So if you look at the SAP landscape of most customers today, they're running DB2, they're running Oracle, they're running MaxDB. These have been SAP systems have grown up over 25 years, right? Some DBs I've never even heard of, right? What they're looking to do is not only just move to SAP HANA, but do this consolidation. And sometimes they're going to consolidate it all into one box, but mostly not. They'll still have smaller pools of boxes around, so maybe they go from 30 down to 10. They want that in a consistent architecture that can scale from small to super large that we have with the CS900 that has all the high-ability mission-critical ability characteristics, even beyond what UNIX has provided. And that's our biggest value prop, plus the expertise. Years and years of expertise in our technology services organization, as well as our enterprise services, to be able to migrate those platforms in a fast, efficient way, move the data, and get you onto a consistent platform. So now that we do have the portfolio, we have the skills and expertise that no one else can bring. Like you say, IBM is there, but they're more motivated to do things around DB2 and other architectures. Oracle's not jumping on, and these start looking at the rest of the pile. There's not too many people that have that application, database, data management, credibility. Again, technologies like 3Bar, the ability to take that database, snapshot it away, back it up, restore it. All those capabilities are built into our Converged System portfolio, be it the 500 or the 900. You don't find a competitor out there that can build out the technologies, the portfolio, as well as the expertise that HP can bring to every customer. All right, Paul, we have to leave it there. Last question is the truck's backing up to the Las Vegas, you know, the Sands. Everything's packed. The bumper sticker on the back as it's leaving Discover 2014. What's that bumper sticker say? It says, Converge, it's the next generation. It's going to help you save valuable dollars. Converge, accept it, it's there. Big data to fast data. All right, keep it right there, everybody. We'll be right back. Thank you, Paul, for coming to theCUBE. It was a pleasure having you. We'll be right back. This is theCUBE, Jeff Frick and I. We're reporting live from Las Vegas. This is HP Discover. We're right back.