MySQL Autopilot delivers nine new machine learning-powered automation capabilities, further improving the performance and scalability of the MySQL Heatwave Service
MySQL HeatWave can now deliver 35X better price/performance compared to Snowflake and 13X better compared to Amazon Redshift with AQUA on industry standard TPC-H benchmark
Tetris.co, Red3i, and FAN Communications migrated from Amazon Aurora to MySQL HeatWave and reported up to 10X performance improvements at less than half the cost
Oracle announced availability of MySQL Autopilot, a new component of MySQL HeatWave service, the in-memory query acceleration engine for MySQL Database Service in Oracle Cloud Infrastructure (OCI). MySQL Autopilot uses advanced machine learning techniques to automate HeatWave which make it easier to use and further improves performance and scalability. No other cloud vendor provides such advanced automation capabilities for their database offerings. Autopilot is available at no additional charge for MySQL HeatWave customers.
MySQL Autopilot automates many of the most important and often challenging aspects of achieving high query performance at scale—including provisioning, data loading, query execution and failure handling. It uses advanced techniques to sample data, collect statistics on data and queries, and build machine learning models using Oracle AutoML to model memory usage, network load and execution time. These machine learning models are then used by MySQL Autopilot to execute its core capabilities. MySQL Autopilot makes the HeatWave query optimizer increasingly intelligent as more queries are executed, resulting in continually improving system performance over time—a capability not available on Amazon Aurora, Amazon Redshift, Snowflake, or other MySQL-based database services.
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MySQL Autopilot includes the following capabilities:
- Auto provisioning predicts the number of HeatWave nodes required for running a workload by adaptive sampling of table data on which analytics is required. This means that customers no longer need to manually estimate the optimal size of their cluster. No other database service provides this capability.
- Auto parallel load can optimize the load time and memory usage by predicting the optimal degree of parallelism for each table being loaded into HeatWave. No other cloud vendor offers this capability.
- Auto data placement predicts the column on which tables should be partitioned in-memory to help achieve the best performance for queries. It also predicts the expected gain in query performance with the new column recommendation. This minimizes data movement across nodes due to suboptimal choices that can be made by operators when manually selecting the column. No other database service provides this capability.
- Auto encoding can determine the optimal representation of columns being loaded into HeatWave, taking the queries into consideration. This optimal representation provides the best query performance and minimizes the size of the cluster to minimize costs.
- Auto query plan improvement learns various statistics from the execution of queries and can improve the execution plan of future queries. This improves the performance of the system as more queries are run. No other database service provides this capability.
- Auto query time estimation can estimate the execution time of a query prior to executing the query. This provides a prediction of how long a query will take, enabling customers to decide if the duration of the query is too long and instead run a different query.
- Auto change propagation intelligently determines the optimal time when changes in MySQL Database should be propagated to the HeatWave Scale-out Data Management layer. This helps ensure that changes are being propagated at the right optimal cadence. No other cloud vendor offers this capability.
- Auto scheduling can determine which queries in the queue are short running and prioritize them over long running queries in an intelligent way to reduce overall wait time. Most other databases use the First In, First Out (FIFO) mechanism for scheduling.
- Auto error recovery provisions new nodes and reloads necessary data if one or more HeatWave nodes is unresponsive due to software or hardware failure.
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“Oracle’s MySQL Database Service with HeatWave is the only MySQL database that efficiently supports both OLTP and OLAP, enabling users to run mixed workloads or real-time analytics against their MySQL database with 10 to 1,000 times better performance and less than half the cost compared to other analytical or MySQL-based databases,” said Edward Screven, Chief Corporate Architect, Oracle. “MySQL HeatWave is one of the fastest growing cloud services on OCI and an increasing number of customers are moving their MySQL workloads to HeatWave. Today, we are announcing a number of innovations which are the result of years of research and advanced development at Oracle. The combination of these innovations delivers massive improvements in automation, performance and cost—further distancing HeatWave from other database cloud services.”
As part of this announcement, Oracle is also introducing MySQL Scale-out Data Management, which can improve the performance of reloading data into HeatWave by up to 100 times. HeatWave now supports a cluster size of 64 nodes—up from 24 nodes—and is capable of processing up to 32 TB of data—up from 12 TB. These new enhancements further strengthen the price/performance advantages of HeatWave relative to its primary competitors.
HeatWave can offer better performance at a lower price for analytics and mixed workloads compared to all other competitive database and analytics cloud services. Specifically, in tests HeatWave has seen:
- 13 times better price/performance than Amazon Redshift with AQUA—6.5 times faster at half the cost (TPC-H 10TB)
- 35 times better price/performance than Snowflake—7 times faster at 1/5 the cost (TPC-H 10TB)
- 36 times better price/performance than Google Big Query—9 times faster at 1/4 the cost (TPC-H 30TB)
- 15 times better price/performance than Azure Synapse—3 times faster at 1/5 the cost (TPC-H 30TB)
- 42 times better price/performance than Amazon Aurora for mixed workloads—18 times lower latency, and 110 times higher throughput at 42 percent the cost (CH-benCHmark 100G)
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Oracle is making the benchmarking code publicly available, enabling customers to run the benchmarks themselves by visiting here. Oracle also announced that the industry standard TPC-DS benchmark can now be accelerated using HeatWave.
Customers who have migrated from Amazon to MySQL HeatWave on OCI thus far have seen a substantial reduction in their costs and a significant improvement in the performance of their cloud workloads.
Red3i is a leading business intelligence and digital marketing company in the U.S. “We successfully migrated our 6 TB database and in-house digital marketing and media management applications from AWS Aurora to MySQL HeatWave on OCI. That reduced our costs by 60 percent, improved performance for complex queries by more than 1,000X, and overall workloads improved 85 percent,” said Amit Palshikar, Co-Founder and CTO, Red3i. “In addition, we didn’t have to make any changes to our application, automatic recovery has minimized downtime, and we can now scale to thousands of cores because we have an ever-growing need.”
Tetris.co is a marketing technology firm that manages large digital advertising investments for customers in Brazil. “MySQL HeatWave reduced our cloud database costs by 50 percent as compared to using a combination of AWS Aurora and Redshift,” said Pablo Lemos, Co-Founder and CTO, Tetris.co. “We are no longer moving data around so now we have blazing fast, real-real-time insights with no effort. More importantly, scalability has made our expansion plan possible, allowing us to onboard more data and new clients without impact to costs. It’s a dream come true.”
Fan Communications is a $280M marketing and advertising affiliate service in Japan. “We found MySQL HeatWave improved performance by 10 times and significantly dropped our costs after migrating from AWS Aurora. We also did not have to modify our application for a great experience,” said Kanami Suzuki, Developer, FANCOMI.
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Tamara is the leading Saudi Buy-Now-Pay-Later platform. “We recently migrated our production workload from another cloud solution to MySQL HeatWave,” said Chien Hoang, Director of Engineering, Tamara. “Doing so reduced our cost by 3 times and it also significantly accelerated many of our queries. Given the speedup we are observing with HeatWave, we expect that we will be able to enhance our application by writing more complex queries which do not execute in a reasonable amount of time with the other cloud solution.”
Industry analysts commenting on today’s news:
“These new fully transparent benchmarks demonstrate HeatWave’s performance, price and scale advantages over all other MySQL and cloud databases,” said Ron Westfall, Senior Analyst and Research Director, Futurum. “With up to 7 times the performance and 35 times the price/performance of Snowflake — a fraction of the cost — you can see the 5 dozen patents at work with the whiplash-inducing performance of HeatWave. Clearly, the cloud data warehouse market wasn’t ready for this, and now the competition needs to scramble as they grapple for answers.”
“Oracle have shown AWS and Snowflake how to design and architect a true MySQL Cloud Database,” said David Floyer, CTO and Co-founder, Wikibon. “Customers can expect MySQL Heatwave to perform about 7 times faster than Amazon Redshift or Snowflake at 2-5 times lower cost. The benefits against Amazon Aurora are even greater. Enterprises of every size can run a single MySQL database for both OLTP and OLAP and eliminate ETL. Lines of business can plan to integrate in-line real-time analytics with systems of record and radically improve business process automation and costs.”
“The evolution of MySQL continues as Oracle accelerates developer velocity. Oracle previously provided a single unified platform for both OLTP and OLAP, eliminating the need for multiple databases and tools to ETL across databases,” said Holger Mueller, VP and Principal Analyst, Constellation Research. “Now Oracle brings out new innovations which are set to likely disrupt the market, significantly lifting the expectations for what open source cloud databases should be. With machine learning-based automation in Autopilot and scaling in memory, nodes, and storage, Oracle sets developers free to develop next generation applications running on the much faster and cheaper MySQL HeatWave compared to any platform they may try.”
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“Some cloud database providers continue to offer specialized databases for specific workloads, and assume, especially in the open source space, that developers like to manually tinker with parameters to optimize performance,” said Carl Olofson, Research Vice President, Data Management Software, IDC. “Oracle is on a different track, looking to combine database functionality in a single system. It provides database convergence and automation in the open source cloud database service, MySQL HeatWave. Oracle introduced MySQL HeatWave late in 2020, bringing full native cloud support and unifying OLTP and OLAP in one database, which eliminated the need for ETL. In this newly announced version, Oracle has added machine learning-based automation, which takes away the guesswork and manual labor involved in provisioning, data loading, query execution, and failure handling. These automations are also a major factor in HeatWave’s performance and price/performance results as reported in the company’s publicly accessible and repeatable benchmarks, providing metrics which should compare favorably with those of other cloud database service providers.”
“For organizations using MySQL, Oracle has given yet another reason to invest in its HeatWave offering by delivering seven times the performance at 1/5 the cost of solutions such as Snowflake,” said Matt Kimball, Senior Analyst, Data Center Compute, Moor Insights & Strategy. “Oracle continues to align its innovation and resources to the needs of its customers and the market. For those looking to extract the most out of their MySQL environments, HeatWave should be given a hard look.”
“Open source developers who have not yet moved to MySQL Database Service with HeatWave are running out of reasons not to give it a try,” said Marc Staimer, Founder and President of DS Consulting and Wikibon Analyst. “Not only has Oracle simplified their lives with a unified OLTP and OLAP MySQL service, it has also eliminated the need for a separate analytical database or data warehouse and ETLs between them. Plus, now it has delivered unparalleled performance and cost/performance. The latest additions include MySQL Autopilot, which has automated many onerous manual tasks from provisioning to data loading and query execution. Together with massive scale-out capabilities, this combination makes MySQL HeatWave melt down Snowflake and vaporize Amazon Redshift with AQUA.”
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“MySQL is a popular cloud relational database for mid-sized users and applications; but it has traditionally come with some limitations,” said Mark Peters, Principal Analyst and Practice Director, ESG. “Developers must suffer manual database setup and tuning as well as often poor performance running queries. That all changes now: Oracle’s MySQL Database Service with HeatWave addresses those issues – it’s MySQL Autopilot uses advanced ML to automate provisioning, tuning and more, to drive crazy good performance and price/performance. Scalability is enhanced with node and processing capacity increases. With claimed specifications that are so far ahead of its competition as to simultaneously generate a broad grin and some skepticism, Oracle understands that the proof is in the pudding – not only is this open source, but the test case details are all being openly posted, meaning that interested MySQL users that are intrigued by a mix of astounding performance, reduced costs and no need to change applications, can actually go try the pudding for themselves.”
“The latest MySQL HeatWave announcement reaffirms and extends Oracle’s commitment to the open source database market,” said Bradley Shimmin, Chief Analyst, AI Platforms, Analytics, and Data Management at Omdia. “Integrated with MySQL Database and optimized for OCI, HeatWave seamlessly brings together analytic and operational workloads within one database and does without sacrificing scale or performance. More than that, MySQL HeatWave introduces several innovations that promise to greatly elevate MySQL’s price/performance value. For example, by engineering internally developed machine learning algorithms within MySQL HeatWave, Oracle can now automate and optimize database provisioning, data loading, query execution, and failure handling. This is not easy to replicate.”
“The new capabilities that Oracle added to MySQL HeatWave take it to the forefront of open source cloud databases,” said Alexei Balaganski, Lead Analyst, KuppingerCole Analysts. “Not only are several management functions automated with Autopilot, making guesswork obsolete, when they are combined with new scaling enhancements, the resulting price/performance ratio is far beyond other cloud database services. As we mentioned previously, ETL presents significant security threats. HeatWave’s combining OLTP and OLAP into a single, protected database instance can dramatically reduce the potential attack surface, improve security posture, and in the end, avoid a data breach or a compliance fine.”
“For customers looking for an open source cloud data warehouse, MySQL HeatWave provides an in-memory query acceleration engine that delivers substantial competitive advantages over AWS Redshift, Aurora and Snowflake,” said Richard Winter, CEO, Wintercorp.
MySQL HeatWave is also incorporated into the Oracle lake house. OCI Data Catalog is the single catalog for the lake house, including data from MySQL Database Service as well as Oracle Autonomous Database and OCI Object Storage. Lake house users can discover MySQL data through the catalog and move it or analyze it as needed. Several other OCI services such as Oracle Analytics Cloud and Oracle Cloud Data Integration service are also integrated with MySQL HeatWave.
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