Supported versions
Memorystore for Valkey is backed by open-source Valkey software.Memorystore for Valkey supports Valkey versions 7.2, 8.0, and 9.0 (Preview). Thedefault version is 8.0.
You can find out which version your instance uses byviewing details about the instance. You can alsoupgrade the version of an instance to any newer version. For example, youcan upgrade from version 7.2 to 9.0 (Preview). For a history ofMemorystore for Valkey product updates, see theRelease notes.
Important: If you upgrade an instance to version 9.0, then you can't downgradethe instance to an earlier version.Current versions
This table shows the supported Valkey versions and when each version was lastupdated:
| Valkey major version | Last update |
|---|---|
| 9.0 (Preview) | October 21, 2025 |
| 8.0 | October 2, 2024 |
| 7.2 | August 30, 2024 |
Valkey version 9.0
Preview
This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of theService Specific Terms. Pre-GA features are available "as is" and might have limited support. For more information, see thelaunch stage descriptions.
Valkey 9.0's major features focus on performance and scalability enhancements,including hash field expiration for more granular data management.
Performance improvements include memory prefetching for pipelining commands,zero-copy responses for large requests, and single instruction, and multipledata (SIMD) optimizations forBITCOUNT andhyperloglog commands.
The following table outlines Memorystore support of some major featuresintroduced by Valkey 9.0:
| Feature | Description |
|---|---|
| Hash field expiration | This feature introduces finer-grained control over data expiration for individual hash fields, rather than just the entire hash key. |
| Memory prefetching | This feature improves performance by prefetching memory for pipelined commands, potentially increasing throughput by up to 40%. |
| Zero-copy responses | This feature reduces overhead by eliminating data copying for large requests, which can lead to up to a 20% increase in throughput. |
| SIMD optimizations | This feature uses SIMD instructions to accelerate certain commands likeBITCOUNT andhyperloglog, potentially improving throughput by up to 200%. |
| By-polygon support for geospatial indexes | This feature adds support for using polygons in geospatial index queries. |
Valkey version 8.0
The following table outlines Memorystore support of some majorfeatures introduced by Valkey 8.0:
| Feature | Description |
|---|---|
| Asynchronous I/O threading for performance boost | This feature significantly improves performance by enabling parallel processing between the main thread and I/O threads. It offloads I/O tasks to the I/O threads, allowing them to run concurrently with the main thread, and optimizes memory access through efficient command batching. |
| Reliability improvement for cluster scaling operations | This feature significantly improves the reliability and automation of the Valkey cluster re-sharding process by addressing failures during slot migration. These improvements prevent data loss and cluster inconsistencies, ensuring a more resilient system when failures occur. |
| Enhanced memory efficiency through key embedding in the main dictionary | This enhancement significantly improves memory efficiency by embedding keys directly within dictionary entries, eliminating the need for separate key pointers. This change reduces memory overhead and enhances performance, particularly for large datasets. |
| Improved Pub/Sub efficiency by using lightweight cluster messages | This feature introduces a new lightweight cluster message type to enhance the efficiency of Pub/Sub message propagation within a Valkey cluster. The new message type significantly reduces the overhead by minimizing the amount of node information included in each message. |
Valkey version 7.2
The following table outlines Memorystore support of some majorfeatures introduced by Valkey 7.2:
| Feature | Description |
|---|---|
| New command | Introduces the WAITAOF command that blocks the client until a specified numberof Redises have synced all previous write commands to the AOF on disk. |
| Memory optimization | Memory usage is significantly reduced for small list-type and set-type keys, with further optimizations for large sets. Memory management for cluster bus links with many pending messages is improved, and incremental reclamation of OS page cache for RDB files enhances memory efficiency. |
| Performance optimization | Performance improvements include faster ZRANGE replies with integer scores and optimized double replies, particularly for sorted sets. Multi-key commands in cluster mode now execute more efficiently, and workloads without pipelining see improved command processing. |
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Last updated 2026-02-19 UTC.