MySQL HeatWave is the only cloud service that combines transactions, real-time analytics across data warehouses and data lakes, and machine learning in one MySQL Database—without the complexity, latency, risks, and cost of ETL duplication. It's available on OCI, AWS, and Azure.
Get started with MySQL HeatWave and learn best practices to get the most out of it. Ask all your questions, share your thoughts, and connect with experts on the MySQL HeatWave forum!
Getting started with MySQL HeatWave on OCI
Migrate to MySQL HeatWave
Using MySQL on-premises or in another cloud? Confidently migrate to MySQL HeatWave using a proven end-to-end approach. Access free step-by-step guides outlining best practices as well as expert guidance from MySQL engineers and Oracle partners.
Application scenarios and reference architectures
How to set up a LAMP stack with MySQL HeatWave: blog series and webcast
- • Part 1: LAMP Stack Architecture and Deployment Options
- • Part 2: Build the infrastructure (network, application server, database server)
- • Part 3: Install and Configure the LAMP Stack Software
- • Part 4: Installing Additional Software for Developing Web Applications
- • Part 5: Making the LAMP Stack More Scalable, Available and Secure
Watch the webcast (32:00)
|Deploy Drupal with MySQL HeatWave MySQL Blog|
MySQL HeatWave Lakehouse
MySQL HeatWave Lakehouse allows customers to query hundreds of terabytes of data in the object store in a variety of file formats, such as CSV, Parquet, and export files from other databases. Customers can query data in object storage using standard MySQL syntax and combine it with transactional data in the MySQL database in a single query. Querying data in object storage is as fast as querying the database.
MySQL HeatWave Lakehouse (5:57)
Get started with in-database machine learning
'How to' blog series
- • Building your first Machine Learning model with MySQL HeatWave AutoML
- • Train your machine learning models 25x faster with MySQL HeatWave AutoML
- • Explore Explainability in MySQL HeatWave AutoML
- • Using various scoring metrics to evaluate MySQL HeatWave ML models
- • Interactive console for machine learning in MySQL HeatWave
- • Time Series Forecasting with MySQL HeatWave
- • Unsupervised Anomaly Detection with MySQL HeatWave
|Get started with MySQL HeatWave Machine Learning|
MySQL Autopilot and real-time elasticity
MySQL Autopilot provides workload-aware, machine learning-powered automation of various aspects of the application lifecycle. Real-time elasticity enables customers to increase or decrease the size of their HeatWave cluster by any number of nodes without incurring any downtime or read-only time.
Using MySQL HeatWave on AWS
Demo: MySQL HeatWave on AWS (3:45)
Using MySQL HeatWave on Azure
Oracle Cloud Infrastructure Blog
Additional resources and best practices
Free Oracle University courses
'How to' blog series
- • How to Set Up High Availability and Replication inside OCI for MySQL HeatWave
- • MySQL HeatWave Best Practices Series: Schema Design
- • MySQL HeatWave Best Practices Series: Data load to HeatWave with MySQL Autopilot
- • MySQL HeatWave Replication Filters and Sources Without GTIDs
- • Using OCI Serverless Functions and API Gateways to create logical dumps of a MySQL HeatWave Database Service with MySQL Shell