 from Las Vegas, it's theCUBE, covering AWS re-invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. What's good to have you back here on theCUBE as we continue our day three coverage of AWS re-invent. This is our seventh year at this show, by the way. And it was just a little itty bitty thing some seven years ago. It's going to almost 40,000 plus this year. I think most of them are still here enjoying day three. Rebecca Knight with John Walls are now joined by Dan Potter, who is the Vice President of Product Management and Marketing at Attunity. Dan, good to see you. Great to be back at theCUBE. You're a CUBE alum. I am a CUBE alum. Yes, I am. And Rebecca, last year, two Bostonians. So again, I'll try to interject what I can. Right, right, right. You don't speak our language. We can translate. It's all right, Danny. It's okay. We were saying before we got started here, you go to a lot of shows, right? And so everyone has its own personality. It has its own rhythm, its own vibe. I mean, how would you characterize what you're seeing here, especially here we are day three, and it's still alive and thriving? It is absolutely overwhelming. This is my third every year it grows, but I just seem to spend my days going from hotel to hotel, to try to hit the sessions you want to. I feel like I'm always in an Uber. It's just so big. And the keynotes, there are so many new solutions that they're rolling out. It's just the scale is so impressive. Yeah. So what keeps you coming back? I mean, is it the chance to see so many customers in one place? Is it to hear the dizzying number of announcements from Andy Jassy? So I loved Andy's presentation. And the keynote this morning was great. For us, all of our customers are moving to the cloud. I mean, Amazon really is the pioneer of people and their transformation to the cloud. And the success that customers are having with the Amazon platform is just astounding. And to see over the last few years how organizations have overcome some of the technical barriers, some of the perceptual, the regulatory barriers, they're all gone now. And this wave of movement to Amazon, and to Google, and to Azure, it's real, and it's happening, and it's only accelerating. So it's exciting for us. We're a vendor of data integration solutions. So we help customers move their data into the cloud. And it's been great business for us, but it's been really fun connecting with our customers who we've gone through multi-year journeys with them as they're moving to the cloud. So it's fun to see the success that they're having now with all the new technologies in the Amazon stack. It's great. So I want to ask you about the trends in the marketplace, what you're seeing, what you're hearing. As you said, the security, the regulatory, the concerns are pretty much gone now. They are. They've had this aha moment. The cloud is where I want to be. Yes. So what else are you seeing? Well, things continue to change. So if you look over the last few years, if you look at what's happening, all of those barriers are removed, but the technology stack, it's still very much in motion in a positive way. New products are being introduced, like today, if you look at the announcement of a managed Kafka service. So one of the big trends we see is the move for real-time analytics. And to empower real-time analytics, you need real-time data movement infrastructure, and Kafka is becoming an integral part of our customer's data integration fabric. So that trend to real-time analytics and having services like Kafka now on the Amazon platform, really important. So it's... And you've got a Hadoop play, right? I mean, so you're working with Hadoop, you're working with Kafka, as you point out, yeah. Well, Hadoop's a great example of some of the changes that have happened over the last few years. Five years ago, it was all Hadoop. And then all of a sudden, the data lake strategy was Hadoop and S3. And now it's Hadoop S3 and it's Snowflake. You know, there's so many different technologies that are really purpose to solve very particular pain points. This is the excitement for customers to be able to have this array of different technologies and done right if they have an architecture that supports them in moving that data where and when it's needed in whatever timeframe and structuring that information so it's analytics ready, that's the value. And that's some of the real innovations that you've seen over the last few years as this has all started to mature. Yeah, well, I mean, take me through the data decision, if you will. What am I going to leave on prem? What am I going to move into the public cloud? Because, you know, as the volume of data grows, we're talking about trillions of processes within a, you know, within seconds. Yep. You know, that's a big nut to crack for a lot of people. What do I leave put in my legacy system? What do I move over? How reliable is it? What's the latency factor here? How do I make sure everybody gets to it who needs to get to it if it's over here and over here? Exactly. So take us through that. So there are two big use cases that we see. One is analytics workloads. The cloud is a perfect place for analytics. It allows you to create a very large data lake, bring in all kinds of heterogeneous data, bring it together, perform real-time transformation and deliver analytics ready data to a wide variety of different business users and use cases. So the cloud is really well-purposed fit for analytics. If you look at all of the innovations that you've seen this week, a lot in AI and machine learning, a lot in real-time analytics. I mean, this is the elasticity of the cloud and the storage capabilities and the cost benefits of being able to store lots of information and to be able to run different processes, analytic processes, when you need those scaled up and scaled down, perfect fit for analytics. So that one is an absolute no-brainer. We see a lot of people, this is the first choice. The first choice for them is they're moving their analytic processes. The second one we see is customers who have core transactional systems, like mainframe systems. You see this a lot in finance, big banks, insurance companies. These are 20-year-old boxes. I don't want to leave the mainframe, right? Not only are they not leaving the mainframe, but they continue to invest in the mainframe and the mainframe is optimized for those transaction processing systems. But what they're not optimized for is how do I build new customer-facing, web-based applications, mobile applications? And the cloud is the perfect environment to do that. So the way that we marry those two things together and the big trend here is this is where real-time synchronization of data comes in. Every time there's an update on that mainframe system, we can move that change data to the cloud in real-time. So if you're a bank and you want to provide a web-based interface, let me check my account balance. I need a real-time view, but you don't want to write that application against the mainframe. It's too expensive. The processing of a mainframe is too expensive. So if I can replicate that data into the cloud and I've got this whole modern array of tools in the cloud and I can take modern approaches like microservices architectures so I can have different optimized, smaller databases that are purpose for different types of mobile apps that's the other trend that we're seeing. So that's kind of bridging that legacy gap and your question of what data do I leave on-prem and what do I move to the cloud? Those core transaction processing systems they may never move to the cloud or in our lifetime we may not see those. All their databases, other applications are lift and shift movement to the cloud. So things that are a more modern architecture we're seeing a lot of lift and shift directly to the cloud but it's going to be a mix for some time. So I understand you have a new launch of attunity for data lakes and AWS. Tell our viewers a little more about that. So this is exciting. So I'll step back for a moment. We provide real-time data integration and we move that change to data from on-prem into the cloud. Moving the data is the first step and it's an absolute requirement but what really needs to happen in order to get the value from your data lake and cloud you need to be able to not just move the data but shape that data and make it purpose fit and analytics ready. So if a use case is analytics and I want to be able to shape this data into a data mark or I want to create an operational data store for real-time reporting or I'm a data scientist I need a historic data store on a subset of information. Those are the analytic ready data sets that need to be created and we're doing that end-to-end data pipeline. So real-time data movement, shaping that data, making it analytics ready and fully automating that process. So it's a streaming data pipeline process that is really leveraging the best of your core transactional systems, mainframe, SAP, Oracle, legacy apps, files and moving that to the cloud in real-time so you can take advantage of all the wonderful capabilities on the Amazon platform. So we've been talking a lot about the changes in the data integration space and sort of what we're seeing. What are your biggest challenges and biggest opportunities as you're looking to 2019? So the biggest challenge is that there's a lot of moving parts. If you look at, again, you look at the last five years and how many things have changed. As an enterprise architect, they must scratch their head every morning and say, what else is going to change? I thought we had this figured out. But that's, so it's a challenge for us because there's a lot of different targets to support. Different clouds, multi-cloud, multiple technologies. But that's also the opportunity. The opportunity here is that for us to play that role and to help customers move data where and when they need it to whatever technology we're completely agnostic. So if a new technology comes up like a snowflake, great cloud data warehouse built on top of S3, we've seen a lot of customer interest in that and that's been recent. In the last two years out of nowhere, but very large enterprise customers has said, I want to jump on snowflakes. So for them to very quickly say, all right, now I'm going to point my data in addition to Hadoop on-prem, I'm going to point it into the Amazon cloud, load it into snowflake, automatically build out that data warehouse for me and let's get real value. That's the opportunity and the excitement for us. It's never stale. There's always lots of work to do and the types of impact that it's having on our customers. Again, it's really transformative to watch them go from the traditional monolithic, slow traditional warehousing processes to more dynamic, real-time spinning up data marts for business users very, very quickly so business users can have better insights faster, make better decisions quicker. That has the impact that these organizations have been looking for and that's why they're investing so much in the cloud so they can have that business impact and we're really starting to see that. It's almost good news, bad news, right? The good news is things will always change. The bad news is things will always change. Absolutely, but that's what makes it fun. Every year you come here and it's just, there's a buzz. There's always something exciting and there's been some great announcements over the last few days and including ours and it's been fun. Right Dan, thanks for being with us. Happy to be here. Good to have you once again on theCUBE. Thanks for having me. See you soon, I hope down the road. I hope. Dan Potter joining us here on theCUBE, back with more from AWS re-invent after a short break.