Oracle Corp. is adding more wood to the MySQL database fire that it started in 2020 with the introduction of HeatWave.

The company released details today of several new enhancements for its MySQL HeatWave database technology. In an exclusive interview with theCUBE, SiliconANGLE Media’s livestreaming video studio, Nipun Agarwal (pictured), senior vice president of MySQL, Database and HeatWave at Oracle, indicated that the company was adding new functionality to the database in response to continued migration of customers seeking to leverage the service for application support.

“More than half the customers who are coming to MySQL HeatWave are migrating from other clouds,” Agarwal said. “The main reason we are told for why customers are migrating from other databases to MySQL HeatWave are lower cost, better performance, and no change to their application. As customers consolidate more data into MySQL HeatWave, they want to run other kinds of processing with this data.”

Agarwal spoke with theCUBE analyst Dave Vellante as they discussed Oracle’s latest news, how the company used benchmark data to compare HeatWave with database services offered by other vendors and the deployment of HeatWave to other cloud providers, including Amazon Web Services Inc.

Machine learning support

Among the services customers were interested in running using HeatWave was analytics support, according to Agarwal. MySQL users have commonly complained about the technology’s limited analytics capabilities. Oracle is adding new features in this regard.

“We are announcing support for in-database machine learning,” Agarwal said. “Customers who have data inside MySQL HeatWave can now run training, inference and prediction all inside the database without the data or the model ever having to leave.”

Oracle is also taking steps to address a requirement for making calls to other services outside of a database to run machine learning. Oracle’s approach is to keep data inside its MySQL HeatWave environment and employ an automated solution for training models.

“Training is an important part of machine learning, and it impacts the quality of predictions,” Agarwal noted. “Traditionally, customers would employ data scientists to influence the training process and make sure it’s done right. HeatWave machine learning is fully automated; there is absolutely no user intervention required for training.”

Addressing cost and performance

Oracle has also taken steps to press its previously announced cost and performance advantages with HeatWave by significantly increasing the amount of data that can be processed within a cluster.

“We have doubled the amount of data that can be processed per node,” Agarwal said. “If you look at a HeatWave cluster, the size of the cluster determines the cost. By doubling the amount of data that can be processed per node, we have effectively reduced the cluster size. This means it reduces the cost to the customer by half.”

In boosting the amount of data processing per node, Oracle is also enhancing HeatWave’s flexibility by introducing elasticity in real time. If a user needs 70 central processing units, for example, the choice is often either 64 or 128. Oracle is tailoring its solution to meet more precise needs.

“We have now fully automated the process of elasticity,” Agarwal said. “If a user wants to scale up or scale down, the only thing they need to specify is the eventual size of the cluster. The system completely takes care of it transparently. By providing this flexibility with MySQL HeatWave, customers get a custom fit.”

Since the gradual rollout of HeatWave last year, Oracle has published numerous comparisons of its MySQL database with others in the market using the open-source decision support benchmark TPC-H. The company has followed a similar process with its latest announcements, posting the results in an open GitHub repository late last week.

“We have run the TPC-DS workload on HeatWave and compared it with vendors,” Agarwal told theCUBE. “We have published two benchmarks, one for machine learning and the other for SQL analytics. We have full transparency, and we invite or encourage customers or other service providers to download the scripts, download the benchmarks, and see if they get different results.”

It is no secret that Oracle has been locked in competition with AWS. Its benchmark comparisons of HeatWave include direct comparisons with Amazon Redshift, the cloud giant’s SQL database.

It was therefore notable that in Oracle’s Q3 earnings call earlier this month, Chairman and Chief Technology Officer Larry Ellison indicated that MySQL HeatWave would soon become available in the Amazon Cloud and Microsoft Azure Cloud.

“The reason why Oracle database is the most popular is that Oracle runs on all the platforms; that has been the case from day one,” Agarwal said. “There’s a lot of value in MySQL HeatWave, and we want to make sure we can offer the same value to the customers of MySQL running on any cloud. This shows how confident we are in our offering.”

Here’s the complete video interview, one of many CUBE Conversations from SiliconANGLE and theCUBE:

Photo: SiliconANGLE