Oracle Announces MySQL Autopilot for MySQL HeatWave Service

Oracle MySQL Autopilot

Oracle has 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.

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.

“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)

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.” 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, “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.

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.”

About Shakthi

I am a Tech Blogger, Disability Activist, Keynote Speaker, Startup Mentor and Digital Branding Consultant. Also a McKinsey Executive Panel Member. Also known as @v_shakthi on twitter. Been around Tech for two decades now.

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