Oracle presents MySQL HeatWave on AWS

Austin – Oracle’s MySQL HeatWave is now available on Amazon Web Services (AWS). MySQL HeatWave is the only service that combines OLTP, analytics, machine learning and machine learning-based automation in a single MySQL database. AWS users can now run transaction processing, analytics and machine learning workloads in one service without the need for 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.

“Oracle wants to give customers choice. Many of our MySQL HeatWave customers have migrated from AWS. Others want to continue running parts of their application on AWS. These customers face serious challenges, including the exorbitant data egress fees that charged by AWS and the increased latency when they access a database service running in Oracle’s cloud.” Edward Screven, Chief Corporate Architect at Oracle. “We address these issues while delivering superior performance and value in transactions, analytics and machine learning compared to other database cloud providers – even compared to Amazon’s own databases running on AWS, where you’d think they should have an advantage. We wanted to allow AWS customers to take advantage of MySQL HeatWave innovations without having to move their data off AWS or teach their developers a new platform.”

Johnny Bytes is an innovative digital agency for web and app development based in Germany. “MySQL HeatWave on AWS simplifies our data platform with a consolidated database for transaction processing and analytics,” he said Thomas Henz, CEO of Johnny Bytes. “We have 60-90x faster complex queries compared to AWS RDS and Aurora, generating the real-time analytics we need for targeted multi-channel campaigns. We now have greater scalability to onboard more data and new customers of all sizes, all without additional IT costs.”

As part of the latest news, Oracle is also introducing several new features and benchmarks for MySQL HeatWave on AWS.

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

Native AWS experience: MySQL HeatWave on AWS offers AWS customers a true native experience with millisecond application latency and a rich interactive console. It facilitates schema and data management and runs queries interactively from the console. Users can monitor the performance of their queries and the usage of the provided resources. MySQL Autopilot is also integrated into the interactive console, making it easier to use.

Advanced security features: The MySQL HeatWave service now offers several comprehensive security features that provide further differentiation from Amazon Aurora. These include server-side data masking and decryption, asymmetric data encryption, and a database firewall. With asymmetric data encryption, developers and DBAs can improve the protection of confidential data and introduce digital signatures to confirm the identity of people signing documents. The database firewall provides real-time protection against database-specific attacks such as SQL injections. These features are designed to provide the best possible security for database users, unlike Aurora where the security methods are 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 error handling. Autopilot includes features such as automatic provisioning, automatic parallel loading, automatic encoding, automatic data placement, automatic scheduling, automatic query plan improvement, automatic change propagation, and automatic error handling. Together, these features improve application performance, reduce the cost of predicting the optimal configuration to run a workload, and reduce manual database management. Today, Oracle is introducing additional autopilot features designed for OLTP workloads that further improve MySQL HeatWave’s price/performance ratio compared to Amazon Aurora. Automatic thread pooling provides higher and sustained throughput with high concurrency by determining the optimal number of transactions to execute. The automatic saliency prediction determines the optimal saliency to implement to provide the best cost/performance for OLTP workloads. For a running system, the recommendation may be to continue using the existing flavor, upgrade to a larger flavor to improve performance, or downgrade to reduce costs—depending on which flavor provides the best value for money.

machine learning: HeatWave ML offers in-database machine learning capabilities including training, inference, and explanation. This allows customers to securely apply machine learning to real-time data without the complexity, latencies and costs of ETL. HeatWave ML fully automates the ML lifecycle and stores all trained models in the MySQL database, eliminating the need to move them to a separate machine learning tool or service. No other cloud or open source database provider offers such advanced ML capabilities in the database. On average, HeatWave ML trains models 25x faster than Redshift ML and scales with cluster size. MySQL HeatWave customers can now train models more frequently and keep them updated for better prediction accuracy.

Distributed cloud ready
MySQL HeatWave is available now in multiple clouds, including OCI, AWS and Microsoft Azure in the near future. The solution is part of the Oracle Dedicated Region [email protected] Available on-premises for organizations unable to move their database workloads to the public cloud. Customers also have the option to replicate data from their on-premise MySQL OLTP applications to MySQL HeatWave on AWS or OCI for near real-time analysis. MySQL HeatWave always runs the latest version of the MySQL database. This is not the case with many other MySQL-based services.

“While AWS offers a ‘buffet’ of cloud database services specialized for each data type and function, MySQL HeatWave follows AWS Oracle’s converged database strategy and offers transactions, analytics, machine learning and autopilot automation in one package. This means that AWS users do not have to pay for additional services, additional storage, data egress, connectors and more. For cost-conscious IT teams and developers, MySQL HeatWave on AWS represents a completely new TCO calculation with no additional service costs on AWS and no data egress fees,” said Marc Staimer, senior analyst at Wikibon. “And just as Usain Bolt eclipsed all his competitors and set new world records that remain unbroken to this day, the latest price-performance benchmark results show that MySQL HeatWave on AWS is 7 times better than Amazon Redshift. When you go by cost, the choice is easy.” (Oracle/mc)

Leave a Comment