Oracle MySQL HeatWave is now live on AWS

Oracle has announced that MySQL HeatWave is available on Amazon Web Services (AWS). MySQL HeatWave is the only service that combines OLTP, analytics, machine learning, and machine learning-based automation within a single MySQL database. AWS users can now run transaction processing, analytics, and machine learning workloads in one service, without requiring time-consuming ETL duplication between separate databases such as Amazon Aurora for transaction processing and Amazon Redshift or Snowflake on AWS for analytics and SageMaker for machine learning.

“At Oracle, we have always proceeded with a vision of being a customer centric organization and the availability of MySQL HeatWave on AWS is in continuation to the very same commitment. In India, MySQL has been a critical element in the digitization journey of many of the organizations be it Startups, Digital Native, Enterprise & Public Sector. We were keen to expand the horizon and facilitate faster innovation for the country. Now, with users of AWS being able to leverage the various benefits of MySQL, all the capabilities of MySQL HeatWave are delivered natively on AWS, so such data transfers and associated high egress fees will no longer be necessary. For users with AWS applications using non-HeatWave implementations of MySQL, they can now upgrade to MySQL HeatWave, without needing to change a single line of code. We are sure that it will pave a way towards an exceptional customer experience,” said P Saravanan, Vice-President, Cloud Engineering, Oracle India.

Oracle is also introducing several new capabilities and benchmarks for MySQL HeatWave on AWS -

Unmatched performance and price performance: MySQL HeatWave on AWS is optimized for AWS with a superior architecture that delivers higher performance and lower cost compared to competitive offerings, as demonstrated by industry standard benchmarks. On the 4TB TPC-H benchmark, MySQL HeatWave on AWS delivers price performance that is 7X better than Amazon Redshift, 10X better than Snowflake, 12X better than Google BigQuery, and 4X better than Azure Synapse. For machine learning, MySQL HeatWave on AWS is 25X faster than Redshift ML. On a 10GB TPC-C workload, MySQL HeatWave offers up to 10X higher and sustained throughput compared to Amazon Aurora at high concurrency. All of these fully transparent benchmark scripts are available on GitHub for customers to replicate.

Native AWS experience: MySQL HeatWave on AWS delivers a true native experience for AWS customers through millisecond-level latencies for applications and a rich interactive console. It facilitates schema and data management, and executes queries interactively from the console. Users can monitor the performance of their queries and monitor the utilization of the provisioned resources. MySQL Autopilot is also integrated with the interactive console, making it easier to use.

Advanced security features: MySQL HeatWave service now offers several comprehensive security features which provide additional differentiation with Amazon Aurora. These include server-side data masking and de-identification, asymmetric data encryption, and a database firewall. Asymmetric data encryption enables developers and DBAs to increase the protection of confidential data and implement digital signatures to confirm the identity of people signing documents. Database firewall provides real-time protection against database-specific attacks, such as SQL Injections. These features are designed to provide best in class security for database users and provide a contrast with Aurora, where security methods are layered on top of the database.

MySQL Autopilot: Autopilot provides workload-aware, machine learning-based automation of various aspects of the application lifecycle, including provisioning, data management, query execution, and failure handling. Autopilot features include auto provisioning, auto parallel loading, auto encoding, auto data placement, auto scheduling, auto query plan improvement, auto change propagation, and auto error handling. Combined, these features improve performance of the application, reduce cost by predicting the optimal configuration to run a workload, and reduce manual database administration. Today, Oracle is introducing additional Autopilot capabilities designed for OLTP workloads which further improve MySQL HeatWave price performance compared to Amazon Aurora.

Machine Learning: HeatWave ML provides in-database machine learning capabilities, including training, inference, and explanations. This enables customers to securely use machine learning on real-time data without the complexity, latency, and cost of ETL. HeatWave ML fully automates the ML lifecycle and stores all trained models inside the MySQL database, eliminating the need to move them to a separate machine learning tool or service. It’s available at no additional charge for MySQL HeatWave customers. No other cloud database vendor or open source database provides such advanced ML capabilities inside the database.

Ready for the Distributed Cloud

MySQL HeatWave is available in multiple clouds, including OCI, AWS, and Microsoft Azure in the near future. It’s available on-premises as part of Oracle Dedicated Region Cloud@Customer for organizations that cannot move their database workloads to the public cloud. Customers can also replicate data from their on-premises MySQL OLTP applications to MySQL HeatWave on AWS or OCI to obtain near real-time analytics. MySQL HeatWave is always running the latest version of the MySQL database which is not the case for many of the other MySQL based services.