Vector Database · decision tool

pgvector vs Pinecone — do you need a dedicated vector DB?

pgvector runs in the Postgres you already operate ($0 extra infra, SQL filtering); Pinecone is a managed serverless store that scales huge with a $50/mo floor. Answer your requirements and see which fits — capability decision, not a fabricated per-vector cost race.

Capabilities verified 2026-07-17 against official documentation · fit weights are our estimates (see methodology) · share the URL to share your configuration

As of Jul 2026, for this page's default requirements, pgvector (Postgres) is the clear pick at 86% capability fit (Pinecone: 70%). This is a capability-fit decision, not a price ranking — StackSays does not invent a unified dollar comparison across these tools' incompatible billing units. Change any requirement below and the verdict recomputes.

Your requirements

The verdict updates as you change these. Share the URL to share your answers.

Already run Postgresyou have a Postgres DB (Supabase/Neon/RDS) in the stackVector counthow many embeddings you'll storeRetrieval typepure vector similarity, or hybrid with keywordMetadata filteringfilter results by attributes (tenant, date, tags)Deploymentmanaged SaaS vs run it on your own infraOps capacitycomfort running a separate data serviceAvoid lock-inprefer open source / portable

Clear pick

pgvector (Postgres) (86% fit)

Ranked by capability fit

pgvector (Postgres) vs Pinecone — the tradeoffs that decide it

Reuse existing Postgres: pgvector (Postgres) — Runs inside the Postgres you already operate (Supabase/Neon/RDS) — no new service, $0 extra infra. Pinecone — Adds a separate vector service to run and pay for, on top of your Postgres.

When to pick Pinecone instead: when the lines above where it leads matter more to you than the ones where pgvector (Postgres) leads. Change the inputs to see the ranking flip.

This is a capability-fit decision, not a price ranking — these tools bill in incompatible units (per-search vs per-RAM cluster vs per-PB scanned) and several publish rates only in their own calculators, so StackSays does not invent a unified dollar comparison. Every score above traces to a documented capability; see Data sources below.

At a glance

Tool	Deployment	Open source	Verified
pgvector (Postgres)	Managed or self-hosted	Yes	2026-07-17
Pinecone	Managed only	No	2026-07-17

Where did you land?anonymous, one click

Data sources

Tool	Source	Verified
pgvector (Postgres)	pgvector documentation (capabilities)	2026-07-17
Pinecone	Pinecone documentation (capabilities)	2026-07-17

A monitor re-checks these pages for changes; when a vendor moves a price, the date updates and every verdict recomputes.

Keep deciding

Compare head-to-head

pgvector vs a dedicated vector DB — when is Postgres enough? →pgvector (Postgres) vs Qdrant — for your app, not in general →pgvector (Postgres) vs Milvus / Zilliz — for your app, not in general →pgvector (Postgres) vs Weaviate — for your app, not in general →Pinecone vs Qdrant — for your app, not in general →Pinecone vs Weaviate — for your app, not in general →

Alternatives

pgvector (Postgres) alternatives — ranked for your stack →Pinecone alternatives — ranked for your stack →Qdrant alternatives — ranked for your stack →Weaviate alternatives — ranked for your stack →Chroma alternatives — ranked for your stack →turbopuffer alternatives — ranked for your stack →

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