Pinecone
$1,000 in credits
Save up to $1,000
AI & DataManaged vector database for AI applications, semantic search, recommendation systems, and RAG at any scale.
What you get
- $1,000 in Pinecone credits
- Managed vector database
- Real-time vector indexing
- Metadata filtering
- Hybrid search (vector + keyword)
Who can claim it
AI startup building vector search
Questions
What is a vector database?
A vector database stores numerical representations (embeddings) of text, images, or other data and finds similar items by mathematical distance. When you search 'shoes similar to this one' or 'documents about this topic,' the vector database finds the closest matches by embedding similarity.
How is Pinecone different from pgvector?
Pinecone is purpose-built for vector operations at scale (billions of vectors, sub-100ms queries). pgvector is a PostgreSQL extension that adds vector search to an existing database. Pinecone is faster at scale; pgvector is simpler for small-scale use cases within Postgres.
Is Pinecone free?
Pinecone has a free tier with 1 index and limited dimensions. The $1,000 credit covers the Standard plan for several months.
What is hybrid search?
Hybrid search combines vector similarity (semantic meaning) with keyword matching (exact terms). This produces better search results than either approach alone.
Does Pinecone support metadata filtering?
Yes. Filter vector search results by metadata attributes (category, date, author) in addition to semantic similarity.
How fast is Pinecone?
Sub-100ms query latency for most workloads, even at billions of vectors. Performance scales with index size and query complexity.