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Which vector database should I use? A comparison cheatsheet

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Re: Which vector database should I use? A comparison cheatsheet

#21
post #3

Earlier quoted context omitted.

Wondering why you didn’t include Elasticsearch [0] in your comparison. Also having some benchmark to compare performance would help. [0] https://www.elastic.co/guide/en/elasticsearch/reference/curr...

+1, I've been using OpenSearch (basically Elasticsearch 7.0), and have been pretty happy with the setup so far. OpenSearch specifically has an edge over Elasticsearch because it supports vectors up to 10k dimensions, whereas ES maxes out at indexing 1024 dimensions, which isn't enough to support OpenAI's 1536 dimension vectors. And then there's the benefit of it being well documented / Q&A'd, and able to support regu…

Also if you want to do hybrid retrieval with legacy system in place elasticsearch is a good option. I would like to see some comparison for the hybrid retrieval as well.

Re: Which vector database should I use? A comparison cheatsheet

#22
post #17

That's not so much a comparison, as it is a collection of bland facts about each solution. Those facts may not even be a good basis for making a choice and it doesn't give any guidance on why each of them may be important. It also looses out on qualitative attributes that distinguish some of them from the others. E.g. Weaviate has a lot better DX (in my opinion) than any of the others as, as it handles integration of…

Completely agree. A bunch of "facts" copied from the providers website. Funny they have a conclusion section. You could probably write something better with AI.

Re: Which vector database should I use? A comparison cheatsheet

#24

There needs to be a standard for benchmarking performance of these solutions. Milvus qps seems to be in a completely different tier of performance than the rest.

Try the original data source

https://github.com/erikbern/ann-benchmarks

Re: Which vector database should I use? A comparison cheatsheet

#27
post #17

That's not so much a comparison, as it is a collection of bland facts about each solution. Those facts may not even be a good basis for making a choice and it doesn't give any guidance on why each of them may be important. It also looses out on qualitative attributes that distinguish some of them from the others. E.g. Weaviate has a lot better DX (in my opinion) than any of the others as, as it handles integration of…

Completely agree. A bunch of "facts" copied from the providers website. Funny they have a conclusion section. You could probably write something better with AI.

That article’s conclusion reads like AI content.

As an aside, I’m not sure if I’ve just made a low value comment. If someone comes to the comments first, I hope they’re informed of my conclusion and take that into consideration before clicking through. I wonder how dang feels about these sorts of comments.

Re: Which vector database should I use? A comparison cheatsheet

#29
post #3
post #2

I have prepared this comparison table to help me choose a vector database. I am sharing it here, hoping it may assist you in your projects as well. Main comparison points: cost at scale, compliance, and queries per second (QPS).

Wondering why you didn’t include Elasticsearch [0] in your comparison. Also having some benchmark to compare performance would help. [0] https://www.elastic.co/guide/en/elasticsearch/reference/curr...

I guess because ES/OS are text search engines and not vector databases. Some benchmarks: https://qdrant.tech/benchmarks/
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