Vector Search in AWS

I need to create a Vector database in AWS. I was using Pinecone in my POC, but for safety reasons the company need something inside AWS. I saw some people recommending to use OpenSearch, but I read in a blog that OpenSearch don't really do Vector Search

> Documented in
> https://www.elastic.co/blog/text-similarity-search-with-vectors-in-elasticsearch
> the approach to vector search has exactly the same limitation as what
> we observed with Solr: it will retrieve all documents that match the
> search criteria (keyword query along with filters on document
> attributes), and score all of them with the vector similarity of
> choice (cosine distance, dot-product or L1/L2 norms). That is, vector
> similarity will not be used during retrieval (first and expensive
> step): it will instead be used during document scoring (second step).
> Therefore, since you can’t know in advance, how many documents to
> fetch to surface most semantically relevant, the mathematical idea of
> vector search is not really applied.

Does any one know any alternative, or is OpenSearch the best we can do in AWS? I read some people talking about using DynamoDB too, but I didn't fully understand how it work. If any one have any ideas or suggestions I would really appreciate.

Souce: https://towardsdatascience.com/speeding-up-bert-search-in-elasticsearch-750f1f34f455

try some newer ones like qdrant, weaviate, milvus . A lot easier to use and less resource hungry than opensearch.

Amazon OpenSearch has a vector based search plugin called as kNN and has experimental features to allow users to perform semantic search.

Reference: K-NN <br/>
AWS K-NN <br/>
Semantic Search feature

Pls take a look at https://docs.datastax.com/en/astra-serverless/docs/vector-search/cql.html You can get super fast and high recall ANN out of Astra Vector powered by Apache Cassandra. Here is a sample query

SELECT * FROM vsearch.products 
ORDER BY item_vector ANN OF [0.15, 0.1, 0.1, 0.35, 0.55]
LIMIT 1;