APIs & DEVELOPER INFRASTRUCTURE
Pinecone
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Pricing
We do not reprint prices. They change too often for that to be honest, and a number on our page with no date is worse than sending you to the source.
How we rated it
What it is
A managed vector database for similarity search: stores embeddings and returns the nearest matches fast, used as the retrieval layer behind AI applications.
Who it is for
Developers building retrieval-augmented systems who do not want to run a vector store themselves.
Where it is strongest
Semantic search over a large collection at low latency, without operating the infrastructure.
Where it falls short
Costs accumulate as the index grows, whether or not anyone queries it. Another service between you and your data. And for modest collections, Postgres with pgvector does the same job inside a database you already run.
Our verdict
Recommended at scale or where you do not want to operate it. Below a few hundred thousand vectors, pgvector is usually the better answer.
Editorial assessment. We earn a commission on some links; it does not change the ranking.