We’ve seen exponential data growth over the past several years. The vast majority of data is generated outside of traditional OLTP applications—via sources such as Internet of Things sensors, connected devices and vehicles, web applications, and telemetry endpoints—and stored in file systems. Organizations want to integrate and analyze this varied external data alongside their internal transactional data. However, it’s often too expensive or complex a process to extract, transform, and load (ETL) this data to a database for analysis. MySQL HeatWave Lakehouse makes it easy for organizations to get valuable real-time insights by combining object storage and database data.
Yes. With HeatWave Lakehouse, MySQL HeatWave provides one cloud database service for transaction processing, real-time analytics across data warehouses and data lakes, and machine learning, all without the complexity, latency, risks, and cost of ETL duplication.
No. HeatWave Lakehouse is 100% compliant with MySQL syntax. Applications that work with MySQL can use HeatWave Lakehouse to query data in object storage without any changes.
There are no changes to MySQL HeatWave’s pricing. You only pay an additional US$20 per TB per month for the data loaded in the MySQL HeatWave storage layer on the object store.
HeatWave’s exceptional performance is a result of its scale-out architecture, which enables massive parallelism to provision the cluster, load data, and process queries with up to 512 cluster nodes. Data from files in the object store is transformed into the HeatWave in-memory optimized hybrid columnar format and the query performance is identical for all supported file formats. Additionally, MySQL Autopilot intelligently samples files to derive the information needed for automation and learns from previously executed queries to improve the execution of subsequent queries.
When loaded into the HeatWave cluster, data from any source is automatically transformed into a single optimized internal format. As a result, querying the data in object storage is as fast as querying the databases.
Yes, MySQL HeatWave runs natively on AWS and MySQL HeatWave Lakehouse is now in limited availability on AWS. With the addition of the Lakehouse capability in MySQL HeatWave, AWS customers can replace five AWS services with one, reducing complexity and obtaining the best price-performance in the industry for analytics.
With HeatWave Lakehouse, AWS customers can query hundreds of terabytes of data in Amazon S3 object storage in various file formats, including CSV, Parquet, Avro, and exports from other databases, without copying the S3 data to the database. They can continue to run applications on AWS with no changes and without incurring unreasonably high AWS data egress fees. AWS customers can also run HeatWave AutoML on HeatWave Lakehouse, which enables them to automatically train machine learning models, run inference and obtain explanations on files stored in S3, and run various kinds of machine learning analysis from the interactive MySQL HeatWave console.
Yes, it’s available to Azure customers via the Oracle Database Service for Azure. Azure customers can use MySQL HeatWave Lakehouse running on OCI as if it were an Azure resource. Users connect their Azure subscriptions to their OCI tenancy in just a few clicks. The service then establishes low-latency connectivity between Azure and OCI, deploys MySQL HeatWave on OCI, and provides metrics on Azure. Customers can combine the entire Azure catalog of AI and application services with MySQL HeatWave. There are no charges for the Oracle Interconnect for Microsoft Azure ports or data ingress/egress over the interconnection.
Yes, the MySQL HeatWave migration program provides access to free step-by-step migration guides outlining best practices, technical training resources, and expert guidance from Oracle engineers and Oracle partners.
Absolutely, you can request a free expert-led workshop.
Definitely, and here are a few to get you started.
To learn more, check out all our MySQL blog posts.