KUALA LUMPUR: Oracle recently announced that MySQL HeatWave – the only service that combines OLTP, analytics, machine learning, and machine learning-based automation within a single MySQL database is available on Amazon Web Services (AWS).
With the announcement, 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.
6D Technologies' associate vice president Anish Kumar shared that the MySQL HeatWave on AWS has 139X faster complex queries compared to Amazon RDS and Aurora. The India-based high-tech solution provider in the telecom industry uses MySQL HeatWave for microservices and cloud native product roadmap.
"MySQL HeatWave on AWS has 139X faster complex queries compared to Amazon RDS and Aurora that gives us a great opportunity to simplify our data infrastructure for both OLTP and OLAP with sub-second response time. MySQL HeatWave is a great fit for our microservices and cloud native product roadmap to deliver a superior experience and performance for our customers," said Kumar, adding that the web console is easy to be configured and provides them with the visibility to workload-related performance metrics and interactive reporting.
On home front, the new capability will further allow businesses in Malaysia to run analytics, machine learning and automation workloads more efficiently.
"As Malaysia continues its digital transformation and innovation efforts aligned to the MyDigital roadmap, business continuity and organisational efficiency remain key. The availability of MySQL HeatWave on AWS ensures that our customers in Malaysia are able to innovate and improve their business performance regardless of whether they choose to run applications on AWS or Oracle Cloud," said Oracle Malaysia managing director, Fitri Abdullah, in a statement.
As part of the announcement, Oracle is also introducing several new capabilities and benchmarks for MySQL HeatWave on AWS.
MySQL HeatWave on AWS is optimised 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 seven-times better than Amazon Redshift, 10-times better than Snowflake, 12-times better than Google BigQuery, and four-times better than Azure Synapse.
For machine learning, MySQL HeatWave on AWS is 25-times faster than Redshift ML.
On a 10GB TPC-C workload, MySQL HeatWave offers up to 10-times 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.
It also 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 utilisation of the provisioned resources.
MySQL Autopilot is also integrated with the interactive console, making it easier to use.
The 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 security for database users and provide a contrast with Aurora, where security methods are layered on top of the database.
Autopilot provides workload-aware, machine learning-based automation of various aspects of the application lifecycle, including provisioning, data management, query execution, and failure handling.
Its 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, reduce cost, and reduce manual database administration.
Oracle also introduced additional Autopilot capabilities designed for OLTP workloads.
Auto thread pooling provides higher and sustained throughput at high concurrency by determining the optimal number of transactions which should be executed. Auto shape prediction on the other hand, determines the optimal shape which should be provisioned to provide the best price performance for OLTP workloads. In a running system, the recommendation could be to continue using the existing shape, to upgrade to a larger shape for better performance or to downgrade to a smaller shape to reduce costs—whichever shape provides the best price performance.
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. On average, HeatWave ML trains models 25-times faster than Redshift ML and scales with the cluster size. MySQL HeatWave customers can now train models more often and keep them updated for increased prediction accuracy.
The MySQL HeatWave application 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 organisations 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.
"While AWS offers a smorgasbord of cloud database services specialised for each data type and capability, MySQL HeatWave on AWS follows Oracle's converged database strategy—offering transaction, analytics, ML, and Autopilot automation all in one.
"For AWS users, this means no charges for add-on services, extra storage, data egress fees, connectors, and more. For cost conscious IT teams and developers, MySQL HeatWave on AWS represents a whole new TCO calculation with zero cost for what are add-on services on AWS and no data egress fees," said Wikibon's senior analyst, Marc Staimer, adding that the latest price performance benchmark results demonstrate that MySQL HeatWave on AWS is seven-times better than Amazon Redshift.