Redis Vector Sets, my work for the last year, I believe address many of such points:

1. Updates: I wrote my own implementation of the HNSW with many changes compared to the paper. The result is that the data structure can be updated while it receives queries, like the other Redis data types. You add vectors with VADD, query for similarity with VSIM, delete with VREM. Also deleting vectors will not perform just a thumbstone deletion. The memory is actually reclaimed immediately.

2. Speed: The implementation is fast, fully threaded reads, partially threaded writes: even for insertion it is easy to stay in the few hundreds of ops/sec, and querying with VSIM is like 50k ops/sec in normal hardware.

3. Trivial: You can reimplement your use case in 10 minutes including learing how it works.

Of course it costs some memory, but less than you may guess: it supports quantization by default, transparently, and for a few millions of elements (most use cases) the memory usage is very low, totally affordable.

Bonus point: if you use vector sets you can ask my help for free. At this stage I support people using vector sets directly.

I'll link here the documentation I wrote myself as it is a bit hard to find, you know... a README inside the repository , in 2025, so odd: https://github.com/redis/redis/blob/unstable/modules/vector-...

P.S. in the README there is stale mention about replication code being not really tested. I filled the gap later and added tests, fixed bugs and so forth.