MySQL HeatWave is the in-memory query acceleration engine for Oracle Cloud Infrastructure’s (OCI) MySQL Database Service. Oracle has now announced MySQL Autopilot which applies machine learning to automate HeatWave, making it easier to use and further improve its performance and scalability.
Autopilot is available at no additional charge for MySQL HeatWave customers.
Autopilot automates many of the most important and often challenging aspects of achieving high query performance at scale. This includes provisioning, data loading, query execution, and failure handling. It uses advanced techniques to sample data, collect statistics on data and queries, and build machine learning models using Oracle AutoML to model memory usage, network load and execution time.
These machine learning models are then used by MySQL Autopilot to execute its core capabilities, resulting in continually improved system performance from the HeatWave query optimiser.
Oracle states this capability is not available on competing products such as Amazon Aurora, Amazon Redshift, Snowflake, or other MySQL-based database services.
The nine new automations Autopilot provides are:
- Auto provisioning to predict the number of HeatWave nodes required for running a workload - eliminating manual effort in estimating the optimal size of the cluster
- Auto parallel load to optimise the load time and memory usage by predicting the optimal degree of parallelism for each table being loaded into HeatWave
- Auto data placement to predict the column on which tables should be partitioned in memory to achieve the best query performance.
- Auto encoding to determine the optimal representation of columns being loaded into HeatWave
- Auto query plan improvement to feed statistics from query executions back into improving the execution plan of future queries
- Auto query time estimation to predict the execution time of a query prior to executing it, allowing customers to decide if it is too long and to alter their query
- Auto change propagation to intelligently determine the optimal time when changes in the MySQL database should be propagated to the HeatWave scale-out data management layer
- Auto scheduling to determine which queries in the queue are short running and prioritise them over long-running queries in an intelligent way to reduce overall wait time
- Auto error recovery provisions new nodes and reloads necessary data if one or more HeatWave nodes is unresponsive for any reason
“Oracle’s MySQL Database Service with HeatWave is the only MySQL database that efficiently supports both OLTP and OLAP, enabling users to run mixed workloads or real-time analytics against their MySQL database with 10 to 1,000 times better performance and less than half the cost compared to other analytical or MySQL-based databases,” said Edward Screven, Chief Corporate Architect, Oracle. “MySQL HeatWave is one of the fastest-growing cloud services on OCI and an increasing number of customers are moving their MySQL workloads to HeatWave. Today, we are announcing a number of innovations resulting from years of research and advanced development at Oracle. The combination of these innovations delivers massive improvements in automation, performance and cost—further distancing HeatWave from other database cloud services.”
Oracle is also introducing MySQL Scale-out Data Management, which can improve the performance of reloading data into HeatWave by up to 100 times. HeatWave now supports a cluster size of 64 nodes (up from 24) and is capable of processing up to 32 TB of data (up from 12 TB).
Oracle states HeatWave is a better choice for customers than competing products, claiming it offers improved price/performance for analytics and mixed workloads. Oracle says its tests are available for anyone to perform themselves and had these results:
- 13x better price/performance than Amazon Redshift with AQUA—6.5 times faster at half the cost (TPC-H 10TB)
- 35x better price/performance than Snowflake—7 times faster at 1/5 the cost (TPC-H 10TB)
- 36x better price/performance than Google Big Query—9 times faster at 1/4 the cost (TPC-H 30TB)
- 15x better price/performance than Azure Synapse—3 times faster at 1/5 the cost (TPC-H 30TB)
- 42x better price/performance than Amazon Aurora for mixed workloads—18 times lower latency, and 110 times higher throughput at 42% the cost (CH-benCHmark 100G)
MySQL HeatWave is also incorporated into the Oracle lake house. OCI Data Catalog is the single catalogue for the lake house, including data from MySQL Database Service as well as Oracle Autonomous Database and OCI Object Storage. Lake house users can discover MySQL data through the catalogue and move it or analyse it as needed. Several other OCI services such as Oracle Analytics Cloud and Oracle Cloud Data Integration service are also integrated with MySQL HeatWave.
The new features introduced in the latest MySQL HeatWave release are available now on OCI across all 30 Oracle Cloud Regions.