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HotKV
Redis-compatible store that uses every core. AI built in.
A multi-threaded, Redis-compatible in-memory data store written in C++20. Existing clients connect unchanged. Vector search, a semantic cache for LLM response and agent memory run inside the server. Benchmarks with Redis, Valkey and Dragonfly are public.
HotKV is a Redis-compatible in-memory data store written from scratch in C++20. It runs commands on every core of the machine at once instead of one. Same protocol, same clients, nothing to rewrite.
What is different
Vector search (HNSW), a semantic cache for LLM responses and agent memory live inside the server, not as modules or a second service. In a benchmark on four Claude models, HotKV in front of the API cut calls, tokens and cost by about 70% on 3,000 support requests. The cases where cached answers were worse were measured and published as well.
Performance
On a 160 vCPU Azure instance HotKV had the highest throughput on 11 of 12 commands against Redis 8.10.2, Valkey 9.1.2 and Dragonfly 2.0.2. The harness, the raw data and the one command it did not win are all on GitHub.
Try it
HotKV Cloud is in free early access, no card required. HotKV is bootstrapped, so instances are provisioned in batches. Write "Product Hunt" in the use case field to be in the first batch.
Questions about the engine, the benchmarks or the trade-offs are welcome below. Every one gets an answer.
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About HotKV on Product Hunt
“Redis-compatible store that uses every core. AI built in.”
HotKV was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #388 on the daily leaderboard. A multi-threaded, Redis-compatible in-memory data store written in C++20. Existing clients connect unchanged. Vector search, a semantic cache for LLM response and agent memory run inside the server. Benchmarks with Redis, Valkey and Dragonfly are public.
HotKV was featured in Developer Tools (521.5k followers), Artificial Intelligence (481.6k followers) and Database (2.3k followers) on Product Hunt. Together, these topics include over 221.8k products, making this a competitive space to launch in.
Who hunted HotKV?
HotKV was hunted by HotKV Ltd. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how HotKV stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
HotKV Ltd
Hello Product Hunt.
HotKV is a Redis-compatible in-memory data store written from scratch in C++20. It runs commands on every core of the machine at once instead of one. Same protocol, same clients, nothing to rewrite.
What is different
Vector search (HNSW), a semantic cache for LLM responses and agent memory live inside the server, not as modules or a second service. In a benchmark on four Claude models, HotKV in front of the API cut calls, tokens and cost by about 70% on 3,000 support requests. The cases where cached answers were worse were measured and published as well.
Performance
On a 160 vCPU Azure instance HotKV had the highest throughput on 11 of 12 commands against Redis 8.10.2, Valkey 9.1.2 and Dragonfly 2.0.2. The harness, the raw data and the one command it did not win are all on GitHub.
Try it
HotKV Cloud is in free early access, no card required. HotKV is bootstrapped, so instances are provisioned in batches. Write "Product Hunt" in the use case field to be in the first batch.
Questions about the engine, the benchmarks or the trade-offs are welcome below. Every one gets an answer.