Oracle HeatWave is a high performance, highly scalable, in-memory cloud service that lets organizations build and run applications for transaction processing, analytics across data warehouses and data lakes, generative AI, and machine learning from a single service. HeatWave customers can get real-time analytics on their transactional data in MySQL Database without duplicating it via extract, transform, and load (ETL) to a separate analytics database. That reduces security risks and cost while query performance improves via HeatWave’s in-memory accelerator.
For artificial intelligence–powered applications, users can take advantage of an automated, in-database vector store to perform retrieval-augmented generation (RAG), which lets AI answer queries using a company’s own data. Developers and analysts without AI expertise can use in-database large language models (LLMs) for AI development. And businesses can deploy HeatWave on Oracle Cloud Infrastructure (OCI), Amazon Web Services, and Microsoft Azure. HeatWave MySQL executes complex analytics queries on a TPC-H decision-support benchmark faster than Amazon Aurora.
HeatWave also supports the same tools for business intelligence and data visualization as MySQL Database, including Oracle Analytics Cloud, Tableau, and Looker. Here are the top reasons that customers choose HeatWave on OCI over Aurora.
Businesses want to build generative AI applications informed by their own data; HeatWave GenAI lets them do so quickly, easily, and securely. Developers can benefit from the automatic creation of vector embeddings needed for RAG to provide company data that augments built-in LLMs. They can use a combination of SQL statements and vector queries, without moving data from the database. To create the same applications with Aurora requires using different cloud services, so developers must move or integrate data across these services.
Capability and evidence |
HeatWave |
Aurora |
---|---|---|
Can customers build generative AI applications using in-database LLMs?
|
yes |
no |
Can customers automate AI vector creation and processing?
|
yes |
no |
Can the system provide optimized resources to accelerate vector processing?
|
yes |
no |
Can customers use a chat interface for natural language conversations?
|
yes |
no |
Optimized for performance and scalability, HeatWave accelerates MySQL queries. It’s faster than other cloud database services, including Aurora, at lower cost.
See the performance details and learn about the benchmark.
Capability and evidence |
HeatWave |
Aurora |
---|---|---|
Can customers run analytics and complex queries without indexing?
|
yes |
no |
Can customers run ad hoc queries efficiently?
|
yes |
no |
Can the database scale as data volume increases while still maintaining performance?
|
yes |
no |
HeatWave MySQL provides 2,200 times better price-performance than Aurora, as demonstrated by the 4 TB data set TPC-H benchmark.
After Broctagon migrated its CRM system from Aurora to HeatWave on OCI, the Singapore-based fintech increased performance by 30% and reduced costs by 35%.
HeatWave eliminates the risk, cost, and complexity of using separate databases for transactions and analytics. HeatWave MySQL, with its integrated in-memory query accelerator, lets database administrators and developers run OLTP and OLAP workloads directly from the MySQL Database. For a 100 GB mixed workload with OLTP and OLAP queries, HeatWave MySQL is 18 times faster than Aurora. It provides 110 times more throughput than Aurora for OLAP queries while maintaining the same performance.
Capability and evidence |
HeatWave |
Aurora |
---|---|---|
Can customers run combined OLTP and OLAP workloads efficiently using a single database service?
|
yes |
no |
Can customers run real-time analytics workloads on their MySQL Database?
|
yes |
no |
Can customers eliminate the cost, complexity, and risk of ETL by using a single database service?
|
yes |
no |
For Japanese ad network FANCOMI, migrating from Aurora to HeatWave increased performance tenfold for real-time analytics while reducing costs. The company no longer needed to move data to an analytical database nor modify its application to get the performance improvement.
ISVs and enterprises need fast, accurate predictions to improve business results. Customers running MySQL applications can immediately take advantage of HeatWave for real-time analytics, without making any changes to their applications. HeatWave can run existing MySQL applications without the need for recoding, and databases and applications running on HeatWave benefit from the additional features and performance.
Capability and evidence |
HeatWave |
Aurora |
---|---|---|
Can customers process transactions and get real-time analytics in the same database without changing existing applications?
|
yes |
no |
Capability and evidence |
HeatWave |
Aurora |
---|---|---|
Does the database service include built-in machine learning automation for operations?
|
yes |
no |
Does the database service include built-in machine learning automation for auto provisioning?
|
yes |
no |
Does the database service include built-in automation for query plan improvement?
|
yes |
no |
Does the database service include built-in automation for auto scheduling?
|
yes |
no |
With HeatWave AutoML, customers can build, train, and explain machine learning models within HeatWave.
Capability and evidence |
HeatWave |
Aurora |
---|---|---|
Does the database service provide in-database machine learning?
|
yes |
no |
Are all machine learning models explainable, so users can understand and explain how they deliver their output?
|
yes |
no |
Is the ML lifecycle automated?
|
yes |
no |
HeatWave lets businesses speed up queries of their key data and analyze data from transactions as they happen—without cumbersome ETL processes. It can run on Oracle’s cloud, AWS, and Azure. Businesses can take advantage of features such as LLMs that ship inside the database and automatic generation of the vectors needed to perform retrieval-augmented generation, which combines pretrained AI models with companies’ own proprietary data for more accurate, relevant results. Aurora can’t tune itself for OLTP workloads nor improve the execution of queries based on what it’s learned from past ones, contributing to lower absolute performance and lower price-performance than HeatWave.
What makes HeatWave faster than Aurora?
HeatWave stores data in memory to accelerate queries and can scale to thousands of processing cores. The software synchronizes data between object storage and the MySQL Database or both, and an in-memory cluster, caching it in memory and removing reads from disk as a performance bottleneck.
How does HeatWave reduce costs compared to Aurora?
HeatWave eliminates the need for a separate analytics database and complex ETL operations between the two databases. It also eliminates the need for separate ML and generative AI services.
How do the machine learning capabilities of HeatWave compare with Aurora’s?
HeatWave AutoML includes ML models inside the database that business analysts can use to build systems for recommending content or products or running what-if scenarios for decisions without SQL commands or coding. Aurora users need to move data to a separate ML service, such as Amazon SageMaker, to build and train models.
Try HeatWave for free.