HeatWave MySQL Features
A fully managed database service
Improve productivity by automating time-consuming tasks, such as high-availability management, patching, upgrades, and backup, with a fully managed database service. Accelerate application development with instant provisioning of resources.
Built, managed, and supported by the MySQL engineering team
Developers can deliver modern, cloud native database applications with immediate access to the latest features from the MySQL team. MySQL security patches are automatically applied to limit exposure to security vulnerabilities. HeatWave MySQL is 100% compatible with on-premises MySQL for a seamless transition to the cloud without changes to applications.
Interactive console for managing resources, running queries, and monitoring performance
Developers and DBAs can easily create and manage MySQL Database and HeatWave nodes. Within the console, they can access HeatWave Autopilot capabilities, such as auto-provisioning, to determine the optimal configuration of their HeatWave cluster. They can view and administer tables loaded in HeatWave MySQL as well as rapidly build and run queries.
The console also lets developers and DBAs monitor the performance of the MySQL Database node and the HeatWave cluster. They can monitor the use of various hardware resources and diverse query execution metrics.
OCI Database Management for HeatWave MySQL
Oracle Cloud Infrastructure (OCI) Database Management helps prevent outages in applications by providing diagnostics capabilities that help ensure the quick resolution of performance bottlenecks. The service can be used to proactively detect and identify the root cause of HeatWave MySQL performance issues. Integration with OCI Ops Insights helps administrators uncover performance issues, forecast consumption, and plan capacity using ML-based analytics.Built on MySQL Enterprise Edition
HeatWave MySQL is the only MySQL cloud service built on MySQL Enterprise Edition. Advanced features let customers implement additional security measures to protect data throughout its lifecycle and help comply with regulatory requirements.
Asymmetric encryption with key generation and digital signatures
Server-side asymmetric encryption enables developers and DBAs to increase the protection of confidential data using both public and private keys. They can also implement digital signatures to confirm the identity of people signing documents. Developers can encrypt data without modifying current applications.
Hide your data
Data masking and deidentification hide and replace real data values with substitutes; selective masking, random data substitution, blurring, and other functions are available. With data masking and deidentification in HeatWave MySQL, customers reduce the risk of a data breach by hiding sensitive data, which can then be used in nonproduction systems, such as development and test environments. These data masking functions are available when queries are executed on the MySQL Database node or the HeatWave cluster.
Block unauthorized database activities
The HeatWave MySQL database firewall monitors database threats, automatically creates an allowlist of approved SQL statements, and blocks unauthorized database activity. It provides real-time protection against database-specific attacks, such as SQL injections.
High performance, in-memory query accelerator
HeatWave is an in-memory, massively parallel, hybrid columnar query-processing engine. It implements state-of-the-art algorithms for distributed query processing that provide very high performance.
Architected for massive scale and performance
HeatWave massively partitions data across a cluster of nodes, which can be operated in parallel. This provides excellent internodal scalability. Each node within a cluster and each core within a node can process partitioned data in parallel. HeatWave has an intelligent query scheduler that overlaps computation with network communication tasks to achieve very high scalability across thousands of cores.
Optimized for the cloud
Query processing in HeatWave has been optimized for commodity servers in the cloud. The sizes of the partitions have been optimized to fit the cache of the underlying shapes. The overlap of computation with communication tasks is optimized for the network bandwidth available. Various analytics processing primitives use the hardware instructions of the underlying virtual machines (VMs).
Optimized for high transaction rates and connections
HeatWave Autopilot improves the performance of the HeatWave MySQL thread pool, providing a mechanism to optimally use hardware resources for better performance. As a result, HeatWave MySQL delivers higher throughput for OLTP workloads and prevents the throughput from dropping at high levels of transactions and concurrency.
Real-time analytics without ETL
HeatWave enables you to run real-time analytics on data in MySQL Database and object storage without extract, transform, and load (ETL) duplication.
Real-time analytics
Analytics queries access the most current information as updates from transactions automatically replicate in real time to the HeatWave analytics cluster. There’s no need to index the data before running analytics queries. Developers and DBAs also can take advantage of HeatWave for real-time analytics on JSON documents stored in MySQL Database and object storage, accelerating analytics queries on the documents by orders of magnitude.
Eliminate ETL
Eliminate the complex, time-consuming, and costly ETL process and integration with separate analytics database and lakehouse services.
No changes to MySQL applications
HeatWave is a native MySQL solution. Current MySQL applications work without changes.
Use existing business intelligence (BI) and data visualization tools
HeatWave supports the same BI and data visualization tools as MySQL Database, including Oracle Analytics Cloud, Tableau, and Looker.
Improve security
Data at rest and in transit between MySQL Database and the nodes of the HeatWave cluster is always encrypted. There’s no risk of data being compromised during ETL since data isn’t transferred between data stores.
HeatWave Autopilot: Built-in machine learning–powered automation
HeatWave Autopilot provides workload-aware, machine learning–powered automation. It improves performance and scalability without requiring database tuning expertise, increases the productivity of developers and DBAs, and helps eliminate human errors. HeatWave 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. HeatWave Autopilot is available at no additional charge for HeatWave MySQL customers.
HeatWave Autopilot provides numerous capabilities for both HeatWave and OLTP.
- 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 developers and DBAs no longer need to manually estimate the optimal size of their cluster.
- Auto thread pooling lets the database service process more transactions for a given hardware configuration, delivering higher throughput for OLTP workloads and preventing it from dropping at high levels of transactions and concurrency.
- Auto shape prediction continuously monitors the OLTP workload, including throughput and buffer pool hit rate, to recommend the right compute shape at any given time—allowing customers to always get the best price-performance.
- Auto encoding determines 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 improves the execution plan of future queries. This improves the performance of the system as more queries are run.
- Adaptive query optimization uses various statistics to adjust data structures and system resources after query execution has started—independently optimizing it for each node based on actual data distribution at runtime. This helps improve the performance of ad hoc queries by up to 25%.
- Auto data placement predicts the column on which tables should be partitioned in memory to 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.
- Auto compression determines the optimal compression algorithm for each column, which improves load and query performance with faster data compression and decompression. By reducing memory usage, customers can cut costs by up to 25%.
- Indexing automatically determines the indexes that customers should create or drop from their tables to optimize OLTP throughput, using machine learning to make a prediction based on individual application workloads. That helps customers eliminate the time-consuming tasks of creating optimal indexes for their OLTP workloads and maintaining those over time as workloads evolve.
Integrated HeatWave capabilities
Using HeatWave MySQL lets you easily take advantage of a wider set of integrated HeatWave capabilities at no additional cost.
HeatWave Lakehouse
HeatWave Lakehouse lets you query data in object storage, MySQL databases, or a combination of both with record speed. Query processing is done entirely within the HeatWave engine, so you can take advantage of HeatWave Lakehouse for non-MySQL workloads as well as MySQL-compatible workloads.
Learn more about HeatWave Lakehouse
HeatWave AutoML
With in-database machine learning (ML), you don’t need to move data to a separate ML service. You can easily and securely apply ML training, inference, and explanation to data stored both inside MySQL and in the object store. As a result, you can accelerate ML initiatives, increase security, and reduce costs.
Learn more about HeatWave AutoML
HeatWave GenAI
HeatWave GenAI provides integrated, automated, and secure generative AI with in-database large language models (LLMs); an automated, in-database vector store; scale-out vector processing; and the ability to have contextual conversations in natural language—allowing you to take advantage of generative AI without AI expertise, data movement, or additional cost.
Real-time elasticity
Real-time elasticity lets you increase or decrease the size of your HeatWave cluster by any number of nodes without incurring any downtime or read-only time.
Consistent high performance, even at peak times, and reduced costs with no downtime
The resizing operation takes only a few minutes, during which time HeatWave remains online, available for all operations. Once resized, data is downloaded from object storage, automatically rebalanced among all available cluster nodes, and becomes immediately available for queries. As a result, you benefit from consistently high performance, even at peak times, and lower costs by downsizing your HeatWave cluster when appropriate—without incurring any downtime or read-only time.
With efficient data reloading from object storage, you can also pause and resume your HeatWave cluster to reduce costs.
No overprovisioned instances
You can expand or reduce your HeatWave cluster to any number of nodes. You aren’t constrained to overprovisioned and costly instances forced by rigid sizing models offered by other cloud database providers. With HeatWave, you pay only for the exact resources you use.
Available in public clouds and your data center
You can deploy HeatWave MySQL on OCI, AWS, or Azure. You can replicate data from on-premises OLTP applications to HeatWave MySQL to get near real-time analytics and process vector data in the cloud. You also can use HeatWave MySQL in your data center with OCI Dedicated Region.
HeatWave MySQL on AWS delivers a native experience for AWS customers. The console, control plane, and data plane reside in AWS.