Oracle looks to grow multi-model database features

Perhaps no single vendor or database platform over the past three decades has been as pervasive as the Oracle database.

Much as the broader IT market has evolved, so too has Oracle's database. Oracle has added new capabilities to meet changing needs and competitive challenges. With a move toward the cloud, new multi-model database options and increasing automation, the modern Oracle database continues to move forward. Among the executives who have been at Oracle the longest is Juan Loaiza, executive vice president of mission critical database technologies, who has watched the database market evolve, first-hand, since 1988.

In this Q&A, Loaiza discusses the evolution of the database market and how Oracle's namesake database is positioned for the future.

Why have you stayed at Oracle for more than three decades and what has been the biggest change you've seen over that time?

Juan Loaiza

Juan Loaiza: A lot of it has to do with the fact that Oracle has done well. I always say Oracle's managed to stay competitive and market-leading with good technology.

Oracle also pivots very quickly when needed. How do you survive for 40 years? Well, you have to react and lead when technology changes.

Decade after decade, Oracle continues to be relevant in the database market as it pivots to include an expanding list of capabilities to serve users.

The big change that happened a little over a year ago is that Thomas Kurian [former president of product development] left Oracle. He was head of all development and when he left what happened is that some of the teams, like database and apps, ended rolling up to [Oracle founder and CTO] Larry Ellison. Larry is now directly managing some of the big technology teams. For example, I work directly with Larry.

What is your view on the multi-model database approach?

Loaiza: This is something we're starting to talk more about. So the term that people use is multi-model but we're using a different term, we're using a term called converged database and the reason for that is because multi-model is kind of one component of it.

Multi-model really talks about different data models that you can model inside the database, but we're also doing much more than that. Blockchain is an example of converging technology that is not even thought about normally as database technology into the database. So we're going well beyond the conventional kind of multi-model of, Hey, I can do this, data format, and that data format.

Initially, the relational database was the mainstream database people used for both OLTP [online transaction processing] and analytics. What has happened in the last 10 to 15 years is that there have been a lot of new database technologies to come around, things like NoSQL, JSON, document databases, databases for geospatial data and graph databases too. So there's a lot of specialty databases that have come around. What's happening is, people are having to cobble together a complex kind of web of databases to solve one problem and that creates an enormous amount of complexity.

With the idea of a converged database, we're taking all the good ideas, whether it's NoSQL, blockchain or graph, and we're building it into the Oracle database. So you can basically use one data store and write your application to that.

The analogy that we use is that of a smartphone. We used to have a music device and a phone device and a calendar device and a GPS device and all these things and what's happened is they've all been converged into a smartphone.

Are companies actually shifting their on-premises production database deployments to the cloud?

Loaiza: There's definitely a switch to the cloud. There are two models to cloud; one is kind of the grassroots. So we're seeing some of that, for example, with our autonomous database that people are using now. So they're like, 'Hey, I'm in the finance department, and I need a reporting database,' or, 'hey, I'm in the marketing department, and I need some database to run some campaign with.' So that's kind of a grassroots and those guys are building a new thing and they want to just go to cloud. It's much easier and much quicker to set up a database and much more agile to go to the cloud.

The second model is where somebody up in the hierarchy says, 'Hey, we have a strategy to move to cloud.' Some companies want to move quickly and some companies say, 'Hey, you know, I'm going to take my time,' and there's everything in the middle.

Will autonomous database technology mean enterprises will need fewer database professionals?

Loaiza: The autonomous database addresses the mundane aspects of running a database. Things like tuning the database, installing it, configuring it, setting up HA [high availability], among other tasks. That doesn't mean that there's nothing for database professionals to do.

Like every other field where there is automation, what you do is you move upstream, you say, 'Hey, I'm going to work on machine learning or analytics or blockchain or security.' There's a lot of different aspects of data management that require a lot of labor.

One of the nice things that we have in this industry is there is no real unemployment crisis in IT. There's a lot of unfilled jobs.

So it's pretty straightforward for someone who has good skills in data management to just move upstream and do something that's going to add more specific value then just configuring and setting up databases, which is really more of a mechanical process.

This interview has been edited for clarity and conciseness.