Good day. My name is Andrea, and I will be your conference operator today. At this time, I would like to welcome everyone to the Emerging Trends in Data Management webcast. I would now like to turn the call over to your host, Mr. Ken Bond, Vice President of Investor Relations. You may begin, sir.
Thank you, operator. Hello, everybody. Thank you for joining us today for Oracle's Executive Access for Investors, an educational webcast series hosted by Oracle. Today is Tuesday, July 22nd, 2014. Joining us today is Andy Mendelsohn, Executive Vice President, and Equity Research Analyst, Karl Keirstead from Deutsche Bank. Today, Andy will discuss emerging trends in data management technology. Please note that Andy will not be discussing any information today that is not already publicly available. At the conclusion of the presentation, we'll turn the webcast over to Karl, who will be leading our Q&A session today. You can submit a question any time during the presentation by clicking on the Ask a Question button on your web browser. Please keep in mind that we will not comment on business for the current quarter.
As a reminder, the matters we'll be discussing today may include forward-looking statements, and as such, are subject to risks and uncertainties that we discuss in detail in our documents filed with the SEC. Specifically, the most recent reports on Form 10-K and 10-Q, which identify important risk factors that could cause actual results to differ from those contained in forward-looking statements. You're also cautioned not to place undue reliance on these forward-looking statements, which reflect our opinions only as of the date of today. Please keep in mind that we're not obligating ourselves to revise, update, or publicly release the results of any revisions of these forward-looking statements in light of new information or future results. Lastly, unauthorized recording of this webcast is not permitted. With that, I'll turn the webcast over to Andy. Andy?
Okay, thanks, Ken. Good morning, everybody. I wanted to do a few things today. We just are going to talk for about 15 minutes and then do Q&A. A couple of weeks ago, we talked about one of our innovations in memory database space. Today, I'm just going to talk a little bit about a few other areas we're working on. The key message is there's a huge amount of innovation going on in the database space, whether it's relational databases or non-relational databases of various sorts. I'm going to focus on some of the innovations we're doing in Oracle. Some of them are in our Oracle Database, and some of them are in these other spaces that we're talking about, NoSQL databases, Hadoop.
I think the innovation that's going on there is really interesting because relational databases have been around for years, if anything, the pace of innovation is accelerating after all these years. I think that's an interesting area to talk about. I also just want to talk briefly about unstructured and structured data, because there's a lot of confusion I see in the financial analyst community where I know you guys listen to lots of startup companies who want to go IPO, and they're making all kinds of interesting claims to you, and it's hard to sort of understand what's real and what's not. I think this is one of the spaces where I think it's important to spend a little time and just clarify what's going on there.
Finally, I'll talk a little bit about what we talked about on our webcast yesterday around Big Data SQL. SQL, again, is cool. It's hot. A couple of years ago, everybody was like, "Oh, we don't need SQL. MapReduce is great. It's taken over. NoSQL is great. That's taken over." Now, after a few years, everybody has sort of figured out, hey, we need SQL. It's really critical. Of course, this is really good for Oracle. We are the leaders in the SQL space, and the trend where SQL is now obviously considered important again, it's fashionable again. It's always been important, but now it's back in fashion. It's a really important trend for us. Let's just focus in on Oracle database innovations. Relational database, of course, has existed for 40 years or something.
Oracle has been the leader in this market for at least the last 20 years, if you measure it by market share or revenue, whatever you want to do, or technology. The reason we're the market leader is because we've been the technology leader for a long time here. I'm not going to bore you and go through all the things we've done over the last 20 to 30 years and give you eye charts, but I just want to call out a few things that have been going on that are worthy of noting. The big thing that's been going on that I think a lot of you don't quite understand is that relational databases are this amazing technology that has been able to evolve across all the different computing eras that have occurred over the last 20 years.
We went to the client server era 20 years ago. That's the era of the PC. We went to the internet 10 years ago. We're going to big data in the cloud now. Relational databases, and Oracle relational database in particular, has done a really good job of leveraging all the new opportunities offered by different computing architectures, different hardware technologies that come along to provide our customers a great and transparent path as they move from generation to generation. All these SQL applications that have been written over the years continue to work as you go from one generation to the next.
If you write an Oracle SQL database application for a client-server era, as you move to the internet, you get to take advantage of all the great technologies that we added to the product back then, and you don't have to rewrite your application. The same now as you move to big data in the cloud. This ability to sort of move our customers from one era to the next without forcing them to rewrite their applications is really important, and that is the key reason why relational databases have been so successful. It's one of the key attributes that I think you see missing in a lot of these other data management technologies. I guess I'll call out a couple things maybe that are worth mentioning just because we'll talk about them later in the presentation.
In the '90s, when we went to the client-server era, one of the things we did is we added support for all kinds of data types in relational databases. We went from being strictly relational databases, according to the strict definition back then, where you just store numbers and strings and dates and tables, to being object-relational. We store basically all kinds of data in relational databases, and we can store anything in a relational database that you can store in any other data management system. I'll talk about that a little bit more on the next slide. As we went to the internet era, two big things were happening. You had to scale to meet the needs of these huge e-commerce sites like Amazon, and you had to be available 24 by seven. That's when we added our Real Application Clustering technology.
This is a very unique technology that enables Oracle to both scale out and scale up on servers that are all sorts of hardware that's available on the market today. We also added our high availability technology. It's called Data Guard, and now it's called Active Data Guard. That's very important for doing HADR kinds of technologies. We continue to evolve in the space with adding new kinds of data type support. You may recall XML databases were becoming popular back then, and people were, if you remember 10 years ago, they were saying they were going to take over the database space. XML was going to be the next big thing. Now, moving to the current era, we've got big data, we've got cloud. We're again navigating that transition. With 12c, the release of the database we did a year ago, we added multi-tenancy into the database.
We are the only vendor now really well-positioned to run databases in clouds with very high density. We essentially have virtualized the Oracle Database with this capability, and now all of our ISVs who've written applications for Oracle over these various generations can now very easily move to the internet to provide software as a service using our multi-tenant capability without rewriting their apps. This is a huge breakthrough for the cloud. Finally, big data. You heard our webcast yesterday. We're now innovating in the big data space as well, and I'll talk a little bit about our Big Data SQL a little later and our JSON data type support as well. Let's move to the next slide. I think it's worth just spending a couple minutes on data. Relational databases, NoSQL databases, Hadoop, all store exactly the same sorts of data. There is no difference.
I know a lot of these companies come to you and say, "Oh, we store unstructured data, and relational databases don't do that." It's true that relational databases in 1980 didn't do that, but when we went object relational in the '90s, we extended relational databases to not only store all kinds of data, but we also extended relational databases to intelligently query that data with SQL. I think that's another thing that's not well understood. You can store bits in any kind of database, but you can't always do intelligent things with those bits. That's the other thing relational databases, and Oracle in particular, are really good at. For example, spatial data. This lets you write SQL queries that say, "Find me all the stores within five miles of my current location." You can do that in SQL.
Other databases let you store latitude and longitude, GPS coordinates, but they don't let you do anything intelligent with that kind of data. Oracle has also been moving into the graph space. We support RDF, and we also will be supporting emerging standards in the graph database space as well. I think the very simple message here is we store all the data. The new kind of data type that's now becoming very popular in certain of the NoSQL databases is JSON. JSON stands for JavaScript Object Notation. We are just adding support for that now in the new database release that's coming out this month. Again, we are extending SQL to support JSON so people can do intelligent things with JSON. It's not just storing the bits.
In relational databases, we can now store JSON with intelligence, and SQL has been extended in the ANSI standard and soon the ISO standard to support JSON operations as well. I think with that, let's go on to the next slide. There are a lot of ways of reading this slide, and I think I'm just going to mention a couple of key points. Traditionally, the Oracle Database group has spent a lot of energy innovating in the relational database space. We are now, as you heard on our webcast yesterday, also innovating in other spaces. Hadoop, the NoSQL space, is another space that we're innovating in. I think it's important to understand, because a lot of the financial analysts always ask, "Oh, is Hadoop replacing Oracle?
Is NoSQL replacing Oracle?" That's always their big focus, because that's what all these companies are telling you, that they're replacing Oracle. The reality of what goes on there is that these technologies are very complementary, and when customers use Hadoop and they use NoSQL, in our accounts, they are very often building systems that are combinations of these different technologies working together in interesting ways. The big thing my group is doing is not just innovating in a particular point solution space. We are building innovations that span these technologies, so our customers can build out the systems that they want that aren't just built out of relational databases. Their big data management systems are both relational databases and Hadoop, for example. Their big e-commerce systems are combinations of relational databases and NoSQL databases.
This is very common out there. I think that's the story I think that a lot of the financial community has missed. It's not an either/or thing, it's an and thing. Customers are using all these technologies. They've been using these technologies for many years. NoSQL, in particular, goes back 30 years. The current generation of NoSQL products certainly have evolved and are much improved versions of the index sequential access method, key value technologies that have been around for years and years. They go back years, and our customers have understood for many years, what is the right place to use NoSQL technology versus when to use relational, and how do you integrate them together. I don't necessarily want to go through all the bullets here. Let's see if there's anything worth mentioning.
I think one thing to keep in mind is relational databases are like Swiss Army knives. They pretty much can do pretty much anything the enterprise customers want to throw at them. They can handle any kind of data management capabilities. They can collect any kind of data. They can scale up, they can scale out. They provide SQL as a standard interface, which is very important. SQL is a standard. All the vendors in this space follow that standard. Customers actually have some hope of saying, "Oh, today I'm going to use Oracle for this SQL system. Tomorrow I could use somebody else. I could actually potentially move my application from one to the other." That's a big thing that you see sort of missing in the NoSQL world. Oracle, I think relational databases very uniquely do both transaction processing and analytics.
None of the other technologies that I show on this slide really can do transaction processing to run the business. If you want to run Business Suite or SAP applications that run the business, you need a relational database. There's no argument there. None of these other technologies can do that. Relational databases also uniquely can do a combination of transactional and analytic processing, which is becoming very important, especially as we move to in-memory database. Customers now are very excited that they can both run transactions and do live analytics against the hot transaction data in the same database. Again, that's something uniquely available from relational database technology. Of course, relational databases are very mature technologies, have great security, high availability, far better than you'll see in the other technology spaces. Moving left, NoSQL databases, like I said, have been around for years.
The confusion here is there are no standards. There's 17 different companies coming to talk to you about their NoSQL database. They're all different. They're all proprietary technologies. If you write an application on one of them, you can never have any hope of moving to the other one. They're complete lock-in. I think that's one of the things that people haven't quite understood about this space. It's like there is no thing that's one NoSQL. There's 17 different things that are sort of related. You can categorize them into things like graph databases and key-value stores and document stores. They're loosely sort of similar in some ways, but they're very different from an application developer standpoint. The latest generation of NoSQL databases really grew out of the web space, where companies like Amazon were trying to do very simple data management operations.
For example, storing a shopping cart in Amazon. You want to store the shopping cart, then you want to be able to retrieve it later when the customer decides they want to add more products to the shopping cart, or they want to buy the product. Key-value databases have been built for these very simple things. You put an object into the database, you get it back out by the key, and that's pretty much it. Like I said, there's so many different NoSQL databases out there that it's hard to say one thing that they do, but that's the key thing that they do. The other key thing you'll see in some of them is that they were designed for web scale, which means they not only do scale out on low-cost servers, but they provide this capability called transparent sharding.
That is very important as you go into the web and try to build systems that span the internet. Oracle Databases are used on the internet, like Amazon, for example, uses hundreds of Oracle Databases for running their e-commerce site, and they do sort of manual sharding of Oracle Databases. I think one of the things you'll see over time is relational database will be adding support for this kind of transparent sharding that you're seeing in some of the NoSQL products. Hadoop is something we're going to focus on in the presentation a little later. Hadoop also is a technology for storing all your data at very low cost, scale out technology. A few years ago, the Hadoop community was saying, "MapReduce is the developer API that's going to replace relational databases.
You don't need SQL anymore." Now they've come pretty much full circle and said, "It turns out very few of our customers have skill sets that let them use MapReduce, we need to add SQL." I think the Hadoop community has certainly come around and figured out SQL is really important. We'll be talking about that next. Let's move on to the next slide. Let's go into what's going on in the SQL space. I've always told you SQL is important, relational databases are important, but now you're hearing it from all over the place. Google, they write a lot of data management technology for their own internal use. They have built out relational databases now for their internal users, and you can see on their slide, they basically said they couldn't do business without SQL.
MapReduce paradigm is just too complex for most of their analysts to have any hope of using. Facebook, another big example. They're probably the biggest Hadoop user in the world. They have also now decided to run our business, do our analytics. We need a combination of both Hadoop and relational, massively parallel relational databases to really let our analysts solve their problems. Let's go to the next slide. If you go drill down into the Hadoop world, SQL is rampant. Everybody and his brother is trying to build out a SQL engine that works on data stored in Hadoop HDFS. The other interesting thing about these projects is that almost every one of them is also saying, MapReduce, not only is it hard for developers to code to MapReduce, it's also really slow. It's only good for batch processing. We can't get interactive response.
Pretty much all these SQL engines being built by the Hadoop community bypass MapReduce altogether, and they go straight into the file system. Which is also sort of an interesting proof point about how successful MapReduce has been at replacing SQL. I have a quote here from Mike Olson. He is a good partner of ours in the Hadoop space, and he says the same thing. All his customers are looking for SQL because basically they have skills in the SQL space, and they want to use those skill sets as they analyze data stored in Hadoop. Let's go to the next slide. Yesterday we had a webcast that I hope some of you saw. If you did not see it, of course, it is up on our website, and you can take a look at it at your leisure.
What we talked about there was some innovation we are doing in the Hadoop space. In fact, not just the Hadoop space. We are now delivering Oracle SQL, the same SQL our customers have been using for years, full functional Oracle SQL dialect, no compromise, full Oracle query optimization, full Oracle parallel query algorithm, not only against data stored in Oracle Database, but now we can integrate data that is stored in Oracle Databases, Oracle NoSQL Databases, and Hadoop into a single SQL query. There is a lot of these projects I mentioned earlier that are trying to introduce SQL for data that is stored on Hadoop, HDFS. What we are doing is leapfrogging that. We are saying, well, customers, in order to solve their big data problems, they want to look at data in all their data sources. They do not want information silos. They want information integration.
With our Oracle Big Data SQL, we are now providing the ability to run one SQL statement that runs in a massively parallel fashion across data sources in Oracle Databases, NoSQL, and Hadoop. Again, I welcome you to go to that webcast to see some more details. The next slide, actually, I will talk a little bit about what we did there, because it is very interesting. Oracle, about 5 years ago, introduced a technology called Exadata. Exadata is our engineered system for Oracle Database. The original big sweet spot for Exadata was actually running parallel queries on big data, on big data warehouses. That technology had a capability called Smart Scan. What we did is we basically made this thing called the Exadata Storage Server, which is a scale-out storage technology that runs on low-cost commodity servers.
It lets us take a SQL query and not only just run the SQL query like normally in relational database servers, but also we could take the SQL and push it down into the storage and transform the storage into a massively parallel SQL scan engine. That is what we call the Smart Scan. That is what is available on Exadata. It has been very successful. We now run the biggest data warehouses in the world. We have incredibly high-performance parallel query across that data. It has been very successful in that space. Now what we are doing is bringing the Smart Scan technology down to Hadoop. You can take basically the Smart Scan, so before only ran on Exadata storage, now can run on the Hadoop data nodes.
On Hadoop data nodes, we are supporting not only looking at data that's in HDFS, Hadoop HDFS, but also data that's in our NoSQL Database as well. We can do the same trick we did on Exadata now in the Hadoop world. We will be offering high-performance Smart Scan technology running locally on the node and offering massively parallel Oracle SQL across all the data in both Oracle relational database, Hadoop, and NoSQL. We're offering the full Oracle SQL dialect, the full Oracle SQL query optimizer that we've worked on for 30 years, the full Oracle set of parallel query algorithms, full support for all the structured and unstructured data types that you find across all these different data management systems.
Again, this is why it's really important for relational databases to be able to support all these kind of data types from SQL, because you want to be able to use one dialect of SQL and scan across all the data, no matter where it's located. Another nice trick here is we can extend the very mature database security mechanisms and policies in Oracle databases to now apply to data that's in these other databases as well. This is one of the areas of weakness, I think, in Hadoop and NoSQL, is they don't have very mature security technologies. We now can give customers the ability to limit, if they limit their users' access to SQL. We can enforce all the policies and rules that are available on Oracle databases for security authentication and authorization. We can extend that to our data in Hadoop and NoSQL.
Of course, we offer our set of engineered systems, the Big Data Appliance for Hadoop and NoSQL, and Exadata for relational databases, and we integrate them together through high-speed InfiniBand networks and through our Big Data SQL software to provide customers a complete solution for analyzing their big data. Okay. Moving to the next slide. I just want to close, and this slide sort of summarizes a lot of the innovations that I talked about that are coming out this year. Like I said, the pace of innovation in database technologies has been accelerating, and you can just look at this one slide, and over the first three quarters of this calendar year, there's a huge amount of innovation coming out of my group across all these different database spaces.
We announced that Database 12c Release 1 Patch Set 1 is coming out later this month with our new in-memory database technology. We're also coming out with Key Vault, which is a security mechanism for storing encryption keys and other security information securely in a cloud kind of environment. Oracle's announced our public cloud offering. We already are production today with cloud storage, and we can back up Oracle databases to the cloud, and we'll be coming out with our Oracle Database service on the cloud, on our public cloud, in Q3 of this calendar year. For engineered systems, we announced our latest and greatest X4-2 generation of Exadata, Big Data Appliance, and Oracle Database Appliance towards the end of last calendar year.
You'll be seeing Exadata X4 actually is being announced tomorrow, and we'll be announcing that we actually are already shipping the Exadata X4-8 version of Exadata, where we've upgraded to the latest and greatest chip and disk technologies and are offering, again, huge price performance in that product as well. Then we announced the Oracle Database Backup Logging Recovery Appliance last OpenWorld, and that will be coming out in Q3 this calendar year. Another big important space now is the developer space. If you look at a lot of the NoSQL and Hadoop technologies, NoSQL especially, a lot of that is being driven by developers, especially these web developers. They are very enamored, for example, of JSON as a way of representing data. As I mentioned earlier, we're very active adding support for JSON into the SQL space and into our NoSQL database product as well.
We are coming out with our JSON support in the new version of the database that's shipping in a couple of weeks later this month. Finally, moving into the big data space, we've been coming out very rapidly with new releases of our Big Data Appliance. The latest release that came out in Q2 of this year supports all the latest and greatest technologies on Hadoop, like MapReduce 2 and YARN. Our NoSQL 3.0 release that came out in Q2 is also a very interesting release. We think our product not only is the most enterprise quality and mature technology out there in the NoSQL space, in the key value NoSQL space, but it also basically has all the capabilities that any customer might want in that space.
We've been innovating in various areas like security, and our Big Data SQL is another example where we've been innovating across all these different data management technologies, across Hadoop, NoSQL, and relational database to deliver our customers the ability to run SQL again and basically integrate information that's stored in all these different information silos in a way that they can solve their big data problems. Again, huge amount of innovation coming out of my team in the database space. Just to summarize, where are we here with data management? Oracle relational database has been able to evolve over the different computing generations to meet the needs of our customers. The key thing we do is as customers move their applications to each new generation, they don't have to rewrite them.
They just get the benefit of better performance, better availability, better security as they go from one generation to the next. That's why relational databases have been so successful over the years. As we move to the cloud and big data, we're continuing that evolution. Oracle's multi-tenant technology is out there in our 12c release for the customers on the cloud. Then as we move to big data, of course, our Big Data SQL technology is a very neat technology that lets customers solve their big data analytics problems. I know a lot of you are always concerned when there's some new technology that comes out, and you're wondering, is it a threat to this vendor or that vendor? In this case, I think what you need to understand is when these new technologies come out, they're actually a big opportunity for relational databases.
Relational databases are incredibly good at absorbing or assimilating new technologies that come around over the years. As you're seeing what we're doing here with the JSON technology, Hadoop technology, we are integrating those technologies either into the core relational database platform itself or with technologies that let us span those platforms to deliver unique value to the customers. You're seeing that as well with the in-memory technology. Relational databases are moving very fast into this in-memory database space. You're not seeing other data management capabilities really even closely being able to follow relational database into the in-memory database space. Of course, as customers move into the cloud, we're making all of our technologies for data management available both on-premise and on the cloud. With that, I think I'll be happy to take some questions from Karl.
Great. Thank you, Andy, so much for hosting this call and sharing your thoughts. I think in terms of emerging data management trends, your shareholders are really focused on three key ones, and you've addressed all of them in your presentation. They would be the impact of NoSQL data stores, the impact of Hadoop, and the potential for databases to be deployed in a public cloud model. I'd love to start by hitting on all three, and if we've got time prior to wrapping up at 1:00 P.M. Eastern, I'll see if we have any questions that were emailed to me directly and ask them as well. Andy, maybe we can start with the NoSQL trend.
Your presentation was pretty clear that SQL-based queries and ACID-compliant data stores are still the default preference of large enterprises, but it's also true that the NoSQL market, even if it's not standardized yet, appears to be growing very quickly. I wanted to start by asking you how large you think the NoSQL market opportunity is, and in your judgment, what new use cases beyond the examples you gave might be motivating enterprises to use them? Thank you.
Just on market size, I'm a technologist, I'm not a financial analyst. I'm not going to tell you how big market X is going to be. That's not something I can do. What I can tell you, though, is if you look at the history of database technologies that have come out over the last 20 years that have claimed that they were going to usurp relational databases in various ways or usurp Oracle in various ways, you can look at the size of those markets. I think you can maybe deduce from that how big relational NoSQL database market is going to be. For example, I guess about 10, 15 years ago, XML was the big thing. XML databases were going to take over the world. You can see for yourself how big is that market.
Open source databases, at one point, they were the big threat. MySQL, in particular, was considered a big threat to relational databases. How big is that market? You can look at that market. I think there's no reason to believe NoSQL will be much different. I think from a big picture standpoint, the thing to understand about all new technologies is they go through this thing that some analysts call the hype cycle, where they start out, it's very trendy, everybody's really excited about the new technology. They think it cures cancer and every other world problem. The NoSQL technology is sort of in that space right now. After you go through that phase, you end up in this phase that they call the trough of despair or disillusionment. Because what happens is customers start building applications using these technologies.
They figure out, "Hey, it doesn't cure all the world's problems. In fact, in a lot of ways, it's not as good as what I was using before." We're about to move into that phase, I think, with NoSQL. I think, a couple of years from now, I think you'll have a better read on how big the market's going to be there. I think there are some genuine use cases that people are looking at that some of the NoSQL systems satisfy well. These classic use cases on the internet, where you're building very simple applications to get input, large data objects, JSON data objects in particular. I think you're going to see that relational databases are good at that too. I think you'll see that Oracle's NoSQL technology also is very good at that.
A lot of our customers are going to prefer the enterprise scale, enterprise maturity of products from Oracle to products that they're getting from startup companies. I think there are genuine use cases in that space. I think whether that's a big market or not, I don't know. That market has existed for years. It's not like it's a new market. Like I said, key value stores and document stores are markets that have been around for a while. You can see how big they are. With that, I think that's about all I can say on that question.
Yeah. That's good, Andy. Thanks. For customers that are looking for unstructured data support or cheaper, more flexible data stores, I'm curious if you could just brief us on what options Oracle does have in its suite. I think in your slide deck, you flagged the Oracle NoSQL Database. You mentioned version 3 coming out shortly with JSON support. Maybe you could elaborate on how Oracle helps customers with these new use cases and how your offering differs from the pure play NoSQL vendors.
Yeah. Okay. I think in the NoSQL space, there are a couple of different interesting technologies going on there. JSON, I mentioned earlier, is one of the new very popular data structure, semi-structured technologies for storing data that's popular there. Our approach has got two strategies. One, of course, we're extending the Oracle SQL relational database to support JSON as a new kind of data type that we support there. SQL's been extended, et cetera. Our NoSQL Database also, of course, is a key value store. It can store any kind of value, including JSON documents. I think we're basically giving customers a choice there. They can choose to use one or the other. They can choose to use both in an integrated fashion.
I think that's one of the big values Oracle provides is that we have a very large installed base of relational database customers, and if they want to create a NoSQL store, it's very often going to be integrated into their Oracle relational database. One of the things we are doing is integrating the technologies together. We have a common enterprise manager console that lets you manage across them. We have things like our new Oracle Big Data SQL that lets you run SQL across them. We think that's going to be very attractive to our enterprise customers in this space. I think you're going to see a lot of innovation from Oracle in both that space, where we have very strong relational products, we have very strong NoSQL products, and we can cover all the use cases people are interested in both of those spaces.
Got it. Okay. Andy, if we can move then to the impact of Hadoop on your market. Hadoop certainly appears to be making very solid inroads into enterprises over the last few years, moving from small pilots to live deployments and from basic data storage to more value-add functions. I wanted to ask you two things about Hadoop. One is, are you seeing significantly increased adoption of Hadoop in your customer base? Secondly, a lot of observers, and even Teradata, agree that some EDW workloads can be more effectively stored in and processed in Hadoop, freeing up EDWs for first-class data, if you'd like. I'm curious if Oracle's own data warehouse business is seeing this same impact, and assuming it is, how you might be responding.
I guess I have read some of those earnings call transcripts from Teradata, where they're claiming they're actually seeing huge impact on their business. Teradata obviously is a pure play in this analytic data warehouse space. Oracle spans all the different use cases, we're much more general. We have much broader technology. I don't think we've been observing the same issues that Teradata has been observing, as far as impact on our business. We see Hadoop being used by our customers in the classic ways. Hadoop is a great way of storing lots amount of data at low cost, and so it tends to replace technologies that were used for storing file system technology, storage technologies that were used for that in the past. It's also a really good batch processing engine for doing things like ETL.
Products that used to have their own platforms for doing ETL, I think are being replaced by Hadoop for doing things of that sort. Some ETL is done in relational databases, I think some of that processing that may have been done in relational databases can be done in Hadoop. I think you're seeing maybe a little movement of work there. I think the big thing that our customers are looking for is they want integration of information across all their different data sources. They're not going to move all their data into just one place. It's not going to all be in Hadoop, it's not going to all be in Oracle Databases, and it's not all going to be in NoSQL. It's going to be in all three.
They want technologies like our Oracle Big Data SQL that lets them integrate across their data in a massively parallel fashion so they can do big data analytics against all their data. I think that's the big thing, the big innovation we announced yesterday that we will be bringing to market, and we're very excited about that, I think it really gives us a highly differentiated space now in this whole new world where customers are using all sorts of different kinds of data management technologies. Okay?
Yeah. Actually that's a nice segue, Andy, to a question I had about that Oracle Big Data SQL product. The SQL on Hadoop space, in particular, seems to be pretty hot. As you pointed out in your presentation, a number of smaller vendors are coming out with products, many of them based on open source technology. I'm wondering if you could elaborate for a sec on your product differentiation, and if you could address when Oracle Big Data SQL will be shipping.
Sure. We announced yesterday, I'll address the shipping problem, that Oracle Big Data SQL will be shipping in the third quarter of this calendar year. What's different about it? Number one is what I just mentioned before. We let you run a single SQL statement using Oracle SQL against all of your data, no matter where it's stored. We can do that in a massively parallel fashion. This is very unique. As you said, there's a lot of SQL on Hadoop projects. They let you run SQL on Hadoop data. That's not what customers want to do. They want to run SQL on all their data. We think that's the key differentiation of what we're doing. Number two, they want to do that in a really high-performance way.
I think there are a lot of solutions out there that claim they can do SQL across all your data, but they're very low performance. A lot of them are these old federation technologies that try to use a lot of different products and connect them together in very interesting ways, and they end up with very low performance. They don't have massively parallel processing for processing through the data, so they're very slow. A number of them on Hadoop will generate MapReduce jobs, which as we know, are very slow as well. We don't do that. We are leveraging the Smart Scan technology that we built originally for Exadata. We're using that technology now on Hadoop HDFS data nodes. We can give customers massively parallel performance against their data, no matter where it's located. This is Oracle SQL.
It's not some simple, small dialect of subset of SQL that was built over the last two years. This is a very mature SQL engine with a mature query optimizer, with mature parallel query algorithms. They're all there that lets you run against all of your data. Finally, the last thing is security. Customers can now leverage Oracle's robust security rules and policies that we have for Oracle Database now for their data that's stored on Hadoop and NoSQL.
Got it. Okay. I think, Andy and Ken, we have time before our deadline for one more question, and I want to make sure we hit on the cloud trend. Andy, some organizations are certainly looking for public cloud-hosted database and data warehouse access. We know that AWS offers its Amazon Redshift data warehouse service as well as Amazon RDS, which incidentally gives clients access to Oracle Database products. What's your take on this broader database-as-a-service opportunity? How big do you think it could get, and how is Oracle addressing that?
Well, the cloud, as I mentioned earlier, is a big new computing era trend. This is a huge industry trend. We are very aware of it, and as I mentioned, our Oracle Database 12c product has been completely re-architected to push multi-tenancy into the database to make sure we have the best technology as customers move to both public clouds and private clouds. I think if you look at our enterprise customers today, I think their position is they all want to build private clouds on-premise. They're all doing consolidation onto private clouds. They want database-as-a-service on-premise. I think that's their big short-term area of investment. They are also very interested in public clouds.
If you look at how much real deployment for just database-as-a-service that's going on in public clouds, there's not a lot going on today, but we are pretty confident that there is a big future that's going to be there, and we want to make sure that as customers move to the public cloud, Oracle has the best database-as-a-service offering in the industry. We are working very hard on that, and we have a schema-as-a-service offering today. I mentioned earlier, we have a backup offering today, so you can back up a database on-premise to our cloud. In Q3 of this year, the plan is to come out with a full-fledged database-as-a-service on the Oracle public cloud. When that market really matures is unclear, but whenever that happens, we're going to make sure we have a very strong offering there.
We're putting a lot of investment in to make sure we are well-placed as that market develops.
Thank you, Andy.
Thank you, Karl. To wrap up everybody, we'd like to thank you for joining us today. Also would like to extend a special thanks to Karl for leading the Q&A portion of today's call and posing the questions most often asked by investors. If you have any follow-up questions, please contact the investor relations department here at Oracle. With that, we'll conclude the webcast. Thank you all very much.