Oracle India Technology Head Saravanan on what’s special in MySQL Heatwave Lakehouse

Oracle, a leading company in cloud and relational database management systems, recently announced the general availability of MySQL HeatWave Lakehouse. This new feature allows customers to query data stored in object storage with the same speed as querying data inside the database. 

“We announced MySQL as a distributed database that is available not only in Oracle Cloud but in AWS and Azure and it's going to go on now. Then we built MySQL Heatwave Lakehouse, that helps in queries data, not only from the MySQL database but query data from the object store,” Oracle India's technology head, Saravanan P, said. 

This allows customers to easily handle and query large amounts of data, stored in diverse object store formats like CSV and Parquet. Additionally, it works seamlessly with Amazon's Aurora and Amazon Redshift backups, he added. 

At its core, MySQL HeatWave Lakehouse aims to blend insights from object storage with conventional database data, ensuring swift access to real-time information. 

Saravanan claimed that in terms of performance metrics, “MySQL is nine times faster than Amazon Redshift; 17 times faster than Snowflake; 17 times faster than Databricks; 36 times faster than Google BigQuery.” 

According to him, this technology holds immense promise for enterprises and customers employing MySQL in various cloud environments, like AWS and others. Its integration promises to simplify business records and processes, aligning with a company's key focus areas. 

Since its launch in December 2020, MySQL has gained popularity as a database choice in various sectors. Amid competition, Oracle has tried to position it as more cost-effective compared to alternatives in the market.

In mid-2021, Oracle introduced the second update to MySQL HeatWave, focusing on automating data management through machine learning. With the release of MySQL Autopilot, Oracle continued its progress by integrating machine learning into MySQL HeatWave, creating HeatWave AutoML. This addition empowers HeatWave to independently create, train, optimise, and explain machine learning models in real-time, utilising the data stored within MySQL.