At Google Cloud, we are committed to delivering the best managed experience backed by open source software. Today, we’re announcing the general availability of Memorystore for Valkey 9.1 , which achieves up to 3x queries per second (QPS) at microsecond latency compared to Memorystore for Redis Cluster.

Our support for Valkey dates back to 2024 , when Redis Inc. shifted its licensing away from the permissive open-source BSD license to a dual-license model. In response, Google Cloud, alongside other technology leaders, backed the creation of Valkey, an open-source alternative governed by the Linux Foundation.

Valkey has come a remarkably long way since then, delivering major performance and feature updates that push boundaries far beyond the original fork. Valkey is particularly compelling for organizations scaling AI and microservices to handle millions of concurrent users. Here, backend developers and architects must deliver both massive throughput while also maintaining microsecond latency.

In this blog, let’s take a look at how Valkey 9.1 achieves its performance, new developer capabilities, how to get started, and how customers are using it.

In high-throughput, in-memory datastores, efficient I/O offloading is critical to keeping the main execution loop unblocked. Previously, Valkey assigned client sockets to I/O threads statically in a round-robin fashion, requiring the main thread to continuously poll lists of pending clients to detect completed work.

Valkey 9.1 replaces list-polling with a lock-free, multi-queue messaging architecture that eliminates cross-thread CPU waste and unlocks dynamic work balancing. It involves three complimentary queues:

Main thread to I/O thread queue : Dispatches read and write jobs to a single-producer multi-consumer (SPMC) queue. Free worker threads pull tasks on demand, enabling dynamic work-stealing that prevents thread starvation or hot-spotting.

I/O thread to main thread queue : Worker threads push completed tasks into a multi-producer single-consumer (MPSC) queue. The main thread pops completed work instantly, eliminating busy-wait list iteration.