DynamoDB adds Vector Search

DynamoDB adds Vector Search.

DynamoDB is an impressive tool. A serverless no SQL document DB that comes with sharding/partitioning baked in.

This means it's designed to scale horizontally by default.

So many times a client or potential client comes to me with the same bottlenecks that traditional DBs fall into as they scale up: It is tough to scale horizontally.

DynamoDB doesn’t have that problem. You are forced to partition out of the box, which can be a pain.

Adding in Vector search makes it even more powerful, as you can now use it for AI-powered search.

They boast “single-digit millisecond latency at 99%+ recall,” and that it is “designed for any scale, even trillions of vectors”.

That is wild.

The only drawback I can see, besides a slight learning curve for the native partitioning, is that you have vendor lock into AWS.

Currently, it supports up to 4096 dimensions, which is amazing. The biggest Vector DB index I have built was around 1028.

If I were building an AI-powered search engine, I would strongly consider DynamoDB.

If you are thinking about building an AI-powered search engine, I would love to chat and hear what you are building and what tech you are using.

Let me know in the comments or reach out directly.

~Cheers