Oracle Brings Its MySQL HeatWave Service on Autopilot with Machine-Learning Capabilities

Oracle has just released an update to its MySQL HeatWave service, a query accelerator for its MySQL database. The new MySQL Autopilot feature uses machine learning to automate tasks and make recommendations based on each dataset’s usage patterns. At the same time, the addition of the Heatwave Storage Layer allows constant-time data reloading into Oracle’s services without needing additional analytics databases that are typically more costly than managing only one single large server.

Oracle’s MySQL Autopilot product streamlines the management of databases and improves HeatWave by leveraging machine-learning models that learn from each database instance’s usage pattern. Therefore, the model’s recommendations are more accurate than generic algorithms and can be easily integrated into existing applications without requiring any changes to those systems.

Oracle’s MySQL Autopilot learns from the database’s runtime behaviour to adjust query plans and scheduling. The company published benchmark results suggesting that this automatic plan improvement benefited performance by 40%.

The MySQL Autopilot suggests provisioning and data loading strategies based on the dynamic behaviour of a specific database. It claims that its memory usage suggestions had an accuracy above 96%, and data placement advice improved performance by 25%. The software can explain what factors are driving these recommendations to know why it is making confident choices for your organization.

HeatWave by Oracle is a new layer built on the OCI Object Store that allows constant time data reloading in minutes for customers using an analytics engine. The company announced support of additional query functions, with Heatwave scaling up to 64 nodes and achieving 0.89 scalability factor now encrypted as well all data at rest within MySQL database environment.

One of the other new features provided by MySQL Autopilot is automatic failure recovery. This ensures that any failures will be detected and repaired automatically, sparing you from having to manually get involved in every little detail about your databases anymore.

Key Additions in MySQL Autopilot:

  • Auto provisioning
  • Auto parallel load
  • Auto data placement
  • Auto encoding
  • Auto query plan improvement
  • Auto query time estimation
  • Auto change propagation
  • Auto scheduling
  • Auto error recovery



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Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.

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