The solution makes it easier for customers to get valuable real-time insights by combining their data in object storage with database data
Oracle has announced the general availability of MySQL HeatWave Lakehouse, a solution that allows customers to query object storage data as swiftly as internal database data. It supports various object store file formats, like Parquet and CSV, allowing data from different sources to be combined in one query. This process avoids data duplication in the MySQL database, resulting in enhanced scalability and performance for query processing, cluster provisioning, data loading, and object storage data querying.
“More than 80% of data is stored in file systems and that number is growing. Customers want to integrate and analyze this varied external data with their internal transactional data, but it’s often too complex or too expensive to process,” said Edward Screven, Chief Corporate Architect, Oracle. “MySQL HeatWave Lakehouse makes it easy for customers to get valuable real-time insights by combining their data in object storage with database data while gaining significantly higher query performance and much faster data loading at a lower cost.”
According to the company, the rapid querying of object storage data is demonstrated in a 10 TB TPC-H benchmark, showing MySQL HeatWave Lakehouse performs at the same speed as querying internal MySQL database data. MySQL Autopilot, part of MySQL HeatWave, uses machine learning to improve query execution plans based on performance insights. MySQL HeatWave on Oracle Cloud Infrastructure (OCI) is powered by AMD EPYC™ processors.
“The AMD and MySQL HeatWave engineering teams are closely collaborating to optimize MySQL HeatWave for AMD EPYC processors to take advantage of new processor capabilities,” said Forrest Norrod, Executive Vice President and General Manager of the Data Center Solutions Business Group, AMD. “Thanks to this collaboration, MySQL customers running MySQL HeatWave on AMD EPYC CPU-powered OCI instances benefit from an outstanding price performance advantage for their business-critical workloads, including real-time analytics on massive amounts of data stored in object storage.”
According to Oracle, MySQL HeatWave Lakehouse’s query performance has been demonstrated to be nine times faster than Amazon Redshift, 17 times faster than Snowflake and Databricks, and 36 times faster than Google BigQuery.
It also claims that data loading from the object store is nine times faster than Amazon Redshift, two times faster than Snowflake, six times faster than Databricks, and eight times faster than Google BigQuery.
MySQL HeatWave’s performance is a result of its scalable architecture that allows extensive parallelism in data loading, cluster provisioning, and query processing. Moreover, advancements to MySQL Autopilot automate metadata creation for object files and adapt to object store performance characteristics for optimal results in any OCI region.
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