Oracle releases new machine learning integrations with its MySQL HeatWave cloud service

HeatWave ML fully automates model training, inference, and explanation.

Oracle MySQL HeatWave now supports in-database machine learning (ML) in addition to the previously available transaction processing and analytics—the only MySQL cloud database service to do so. MySQL HeatWave ML fully automates the ML lifecycle and stores all trained models inside the MySQL database, eliminating the need to move data or the model to a machine learning tool or service. Eliminating ETL reduces application complexity, lowers cost, and improves the security of both the data and the model. HeatWave ML is included with the MySQL HeatWave database cloud service in all 37 Oracle Cloud Infrastructure (OCI) regions.

HeatWave ML offers the following capabilities:

  1. Fully Automated Model Training
  2. Model and Inference Explanations
  3. Hyper-Parameter Tuning
  4. Algorithm Selection
  5. Intelligent Data Sampling
  6. Feature Selection

In addition to machine learning capabilities, Oracle released more innovations to the MySQL HeatWave service. Real-time elasticity enables customers to upsize and downsize their HeatWave cluster to any number of nodes, without any downtime or read-only time, and without the need to manually rebalance the cluster. Also included is data compression, which enables customers to process twice the amount of data per node and lowers costs by nearly 50 per cent, while maintaining the same price-performance ratio. Finally, a new pause-and-resume function enables customers to pause HeatWave to save costs. Upon resuming, both the data and the statistics needed for MySQL Autopilot are automatically reloaded into HeatWave.

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