Open-source databases have been gaining ground in recent years as businesses turn away from proprietary software in an effort to reduce costs. But getting there is not always easy.

The open-source Babelfish database translation tool, announced by Amazon Web Services Inc. during the AWS re:Invent event, aims to help organizations in this process, according to Shawn Bice, vice president of databases at AWS.

“You talk to somebody and they will say things like: ‘We’ve built years and years and years of application development against SQL Server, we really don’t like the punitive commercial licensing, and we’re trying to get over to open source but we need an easier way,’” said Bice (pictured). “We’ve thought about that long and hard, and we came up with a wonderful solution.”

Bice spoke with John Walls, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during AWS re:Invent. They discussed AWS announcements regarding databases, how the new Babelfish for Aurora PostgreSQL works and the security issues involved in the data environment. (* Disclosure below.)

A database solution for each business case

Babelfish for Aurora PostgreSQL makes it easier to migrate Structured Query Language databases to the AWS cloud. That means enterprises can now perform database migrations without doing any of the laborious manual work, such as replacing database drivers and rewriting and verifying database requests. The open-source version will be available on GitHub under an Apache 2.0 license.

The adoption of open source is often one of the steps taken by companies that are reconfiguring their databases. In the first stage, they usually move to the cloud, according to Bice. Then they migrate to open source and, after this, start building modern applications for the cloud.

“In that context, they follow the playbook of these early cloud builders, which is you take this big app, you break it into smaller parts, and then they pick the right tool for the right job,” he said. “In the new world that we live in, it really is: Let’s start with the business use case first, understand the access pattern, and then pick the best optimized database storage for that.”

As there are numerous business cases out there, there is also a handful of categories around data models and access patterns. In addition to the traditional relational database, there is, for example, the key-value database, which is highly partitionable and allows horizontal scaling at scales that other types of databases cannot achieve.

“Imagine you order a ride share and you’re trying to track a vehicle every second so … you can see it moving across your phone,” he said. “And now imagine if you were building that app: ‘Are a million people going to do that all at the same time, or 10? So, in that kind of access pattern, a product like DynamoDB is excellent, because it’s designed for basically unlimited scale.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of AWS re:Invent. (* Disclosure: Amazon Web Services sponsored this segment of theCUBE. Neither AWS nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE