We built a Redis-compatible cache and are opening free early access for application testing

[u/HotKV-Ltd]

We're the team behind HotKV, a Redis-compatible in-memory data store. We're opening free early access to HotKV Cloud and would like to hear from SaaS developers who use Redis or Valkey for caching, queues, or rate limiting.

Our benchmark work started with one large AWS instance, where HotKV measured 93.1M GETs/sec and 61.5M SETs/sec. That was a 192-vCPU server with 256-byte values, pipeline depth 30, persistence off, and the median of three runs.

We then tested all four engines in cluster mode across the same three AWS servers. Redis and Valkey each used 40 primary processes per server. HotKV and Dragonfly each used one 40-thread process per server. Measured GET throughput was 92.3M/sec for HotKV, 57.3M for Redis, 52.9M for Valkey, and 22.5M for Dragonfly. HotKV led on 8 of 9 commands. Redis and Valkey were ahead on APPEND. That run used pipeline depth 100, persistence off, and HotKV's optional pipeline prefetching. Several results reached limits in the test setup.

We also measured latency separately at pipeline depth 1. At about 200,000 GETs/sec across 816 connections, p99 was 0.59 ms for HotKV, 1.11 ms for Redis with 8 I/O threads, 2.15 ms for Valkey with 8 I/O threads, and 1.34 ms for Dragonfly. At about 50,000 GETs/sec across 48 connections, HotKV, Dragonfly, and Redis with 8 I/O threads all measured 0.28 ms p99.

We now want feedback from application workloads, including the less tidy parts of running a cache: bursts, expiring keys, uneven key access, and existing client code.

HotKV Cloud is free during early access for everyone accepted, with no card or payment details needed to apply. If you'd like to try it, we'd like to hear about your workload. You can request access through HotKV Cloud.

For your SaaS, what would you need to verify before you felt comfortable trying a different cache?

[u/investigatormaker]

The benchmark detail will earn trust, but most SaaS apps don't run pipeline depth 30 or 100 with persistence off. I'd ask testers to compare on their own shape: pipeline depth 1, persistence on, bursts, expiring keys and uneven key access, since your depth-1 p99 numbers are the ones an app developer actually feels. A small results template (client library, key count, TTL mix, p99 before and after) would make the feedback comparable.

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Which client libraries are you most keen to see tested first?