Pinecone vs pgvector: Which DB is right for your startup?

When picking a vector store for your startup's RAG stack, you generally choose between dedicated vector databases (like Pinecone) or extending your existing relational database (like PostgreSQL with pgvector). ### Pinecone - **Pros**: Fully managed, auto-scaling, highly optimized search structures, quick cold start. - **Cons**: High monthly starting costs, data leaves your core database network boundary. ### pgvector (PostgreSQL) - **Pros**: Same database you use for application data, transaction safety, zero extra cost if already running PG, easy relations. - **Cons**: Must manage indexing manually (e.g. HNSW, IVFFlat), scaling database memory is up to you. For early startups, starting with pgvector inside your relational system keeps infrastructure simple and keeps costs low. As query volumes cross millions, migrating to a dedicated index like Pinecone becomes the logical scaling path.