 Live from San Jose, in the heart of Silicon Valley. It's theCUBE, covering DataWorks Summit 2018. Brought to you by Hortonworks. Welcome back to theCUBE's live coverage of DataWorks here in sunny San Jose, California. I'm your host, Rebecca Knight, along with my co-host, James Kobielus. We're joined by Dan Potter. He is the VP Product Management at Atunity, as also Ali Bajoie, who is the principal partner solutions engineer at Hortonworks. Thanks so much for coming on theCUBE. Pleasure to be here. It's good to be here. So I want to start with you, Dan, and have you tell our viewers a little bit about the company based in Boston, Massachusetts. What Atunity does? Atunity, we're a data integration vendor. We're best known as a provider of real-time data movement from transactional systems into data lakes, into clouds, into streaming architectures. So it's really, it's a modern approach to data integration. So as these core transactional systems are being updated, we're able to take those changes and move those changes where they're needed, when they're needed for analytics, for new operational applications, for a variety of different tasks. So you have a- Change data capture. Change data capture, they are well-known in this space. They have changed data capture, go ahead. We are, yeah. So tell us about the announcement today that Atunity has made at Hortonworks. Yeah, thank you. It's a great announcement because it showcases the collaboration between Atunity and Hortonworks. And it's all about taking the metadata that we capture in that integration process. So we're a piece of a data lake architecture. As we're capturing changes from those source systems, we're also capturing the metadata. So we understand the source systems, we understand how the data gets modified along the way. We use that metadata internally and now we're built extensions to share that metadata into Atlas and to be able to extend that out through Atlas to higher data governance initiatives. So data steward studio into the data plane services. So it's really important to be able to take the metadata that we have and to add to it the metadata that's from the other sources of information. Sure, for more of the transactional semantics of what Hortonworks has been describing and they've baked in to HDP and your overall portfolio, is that true? I mean, that supports those kinds of requirements. Yeah, so with HDP what we're seeing is the EDW optimization play has become more and more important for a lot of customers as they try to optimize what the data that their EDWs are working on. So it really gels well with what we've done here with Hattunity and then on the Atlas side with the integration on the governance side with GDPR and other sort of regulations coming into the plane now, those sort of things are becoming more and more important specifically around the governance initiative. We actually have a talk just on Thursday morning where we're actually showcasing the integration as well. So can you talk a little bit more about that for those who aren't going to be there for Thursday? GDPR was really a big theme at the DataWorks Berlin event. And now we're in this new era and it's not talked about too, too much. And global businesses who have customers in EU but also all over the world are trying to be systematic and consistent about how they manage PII everywhere. So GDPR though is an EU regulation really in many ways it's having ripple effects across the world in terms of practices. Absolutely. And at the heart of understanding how you protect yourself and comply, I need to understand my data and that's where metadata comes in. So having a holistic understanding of all of the data that resides in your data lake or in your cloud metadata becomes a key part of that. And also in terms of enforcing that if I understand my customer data where the customer data comes from the lineage from that then I'm able to apply the protections of the masking on top of that data. So it's really, the GDPR effect has had, it's created a broad scale need for organizations to really get a handle on metadata. So the timing of our announcement just works real well. And one nice thing about this integration is that it's not just about being able to capture the data in Atlas but now with the integration of Atlas and Ranger you can do enforcement of policies based on classifications as well. So if you can tag data as PCI, PII, personal data that can get enforced through Ranger to say that hey only certain admins can access certain types of data. And now all that becomes possible once we've taken the initial steps of the Atlas integration. So with this collaboration it's really deepening an existing relationship. So how do you go to market? How do you collaborate with each other and then also service clients? Yeah, so from an engineering perspective we've got deep roots in terms of being a first class provider into the Hortonworks platform both HDP and HDF. Now last year about this time we announced our support for acid merge capabilities. So the leading edge work that Hortonworks has done in bringing acid compliance capabilities into Hive was a really important one. So our change data capture capabilities were able to feed directly into that and be able to support those extensions. Yeah, we have a lot of really key customers together with Attunity. And maybe as a result of that they're actually our ISV of the year as well which they proudly showcase on their... We're very proud of that. Yeah, it's a nice honor for us to get that distinction from Hortonworks. And it's also a proof point to the collaboration that we have commercially. Our sales reps work hand in hand. When we go into a large organization we both sell to very large organizations. These are big transformative initiatives for these organizations and they're looking for solutions not technologies. So the fact that we can come in, we can show the proof points from other customers that are successfully using our joint solution. That's really, it's critical. And I think it helps that they're integrating with some of our key technologies because that's where our sales force and our customers really see that as well as that's where we're putting in the investment and that's where these guys are also investing. So it really helps the story together. So with Hive we're doing a lot of investment on making it closer and closer to a sort of a real-time database where you can combine historical insights as well as your real-time insights with the new ACID merge capabilities where you can do the inserts, updates and deletes. And so that's exactly what Attunity is integrating with Atlas. We're doing a lot of investments there. That's exactly what these guys are integrating with. So I think our customers and prospects really see that and that's where all the wins are coming from. And I think together there were two main barriers that we saw in terms of customers getting the most out of their data lake investment. One of them was as I'm moving data into my data lake I need to be able to put some structure around this. I need to be able to handle continuously updating data from multiple sources. And that's what we introduced with Attunity Composed for Hive. Building out the structure in an automated fashion. So I've got analytics ready data and using the ACID merge capabilities just made those updates much easier. The second piece was metadata. Business users need to have confidence that the data that they're using, where did this come from? How is it modified? And overcoming both of those is really helping organizations make the most of those investments. How would you describe customer attitudes right now in terms of their approach to data? As we've talked about data is the new oil. So there's a real excitement and a buzz around it. And yet there's also so many high profile cases of breaches and security concerns. So what would you say is that the customers are they more excited or they're more trepidatious? How would you describe the CIO mindset right now? So I think security and governance has become top of minds, right? So more and more the surveys that we've taken with our customers, right? More and more customers are more concerned about security, they're more concerned about governance. The joke is that we talk to some of our customers and they keep talking to us about Atlas, which is sort of one of the newer offerings around governance that we have. But then we ask, hey, what about Ranger for enforcement? They're like, oh yeah, that's a standard now for a dupe, right? So we have Ranger. Now it's a question of how do we get our hooks into the Atlas and all that kind of stuff. So it's definitely, as you mentioned, because of GDPR, because of all these kind of issues that have happened, it's definitely become top of minds. And I would say the other side of that is there's real excitement as well about the possibilities now, bringing together all of this data, AI, machine learning, real-time analytics and real-time visualization. There's capabilities, analytic capabilities now that organizations have never had. So there's great excitement, but there's also trepidation. How do we solve for both of those? And together we're doing just that. As you mentioned, because if you look at Europe, some of the European companies who are more hit by GDPR, they're actually excited that now they can really get to understand their data more and do better things with it as a result of the GDPR initiative. Absolutely. Are you using machine learning inside of a tunity in a Hortonworks context to find patterns in that data? So what we do is, so we enable data scientists to build those models. So we're not only bringing the data together, but again, part of the announcement last year is the way we structure that data in Hive, we provide a complete historic data store. So every single transaction that has happened and we send those transactions as they happen, it's at a big append. So if you're a data scientist, I want to understand the complete history of the transactions of a customer to be able to build those models. So building those out in Hive and making those analytics ready in Hive, that's what we do. So we're a key enabler to machine learning. Making analytics ready rather than do the analytics in the screen. Absolutely. Yeah, the other side to that is that, because they're integrated with Atlas, now we have a new capability called Data Plane and Data Stewards Studio. So that's the idea there is around multi-everything. So more and more customers have multiple clusters, it's whether it's on-prem in the cloud. So now more and more customers are looking at how do I get a single glass pane of view across all my data, right? Whether it's on-prem in the cloud, whether it's IoT, whether it's data at rest, right? So that's where Data Plane comes in and with the Data Stewards Studio, which is our second offering on top of Data Plane, they can kind of get that view across all their clusters. So as soon as the data lands from maternity into Atlas, you can get a view into that across as part of Data Stewards Studio. And one of the nice things we do in Data Stewards Studio is that we also have machine learning models to basically figure out, to do some profiling, to figure out that, hey, this looks like a credit card. So maybe I should suggest this as a tag of sensitive data. And now the end user, the end administration has the option of saying that, okay, yeah, this is a credit card, I'll accept that tag, or they can reject that and pick one of their own. Well, any of this going forward of the attunity, CDC, change data capture capability, be containerized for deployment to the edges in the, in HTTP 3.0. Because it seems, I mean for, you know, Internet of Things, Edge Analytics and so forth, change data capture is absolutely necessary to make the entire, some call it the fog computing, the cloud or whatever, to make it a completely transactional environment for all applications from micro endpoint to micro endpoint. Are there any plans to do that going forward? Yeah, so I think with HTTP 3.0, as you mentioned, right, one of the key factors that was coming into play was around time to value. So with containerization now being able to easily bring third party apps on top of yarn through Docker. I think that's definitely an avenue that we're looking at. Yeah, we're excited about that with 3.0 as well. So that's definitely the cards for us. Great, well, Ali and Dan, thank you so much for coming on theCUBE, it's fun to have you here. Nice to be here, thank you guys. Great to have you. Thank you, it was a pleasure. I'm Rebecca Knight for James Kobielus, we will have more from DataWorks in San Jose just after this.