Pinecone vs Weaviate
Two sides of the vector database decision: managed vector store and open-source vector store. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.
Ask your AI about this, with this page as the source:ChatGPT ↗Claude ↗Perplexity ↗
Which fits you
Choose Pinecone if- You want a hosted index with nothing to operate
Use it whenYou want vector search without running any infrastructure.
Trade-offClosed source and cloud-only, so leaving means re-indexing somewhere else.
Choose Weaviate if- You need an open-source store with heavy filtering or hybrid search, self-hosted or managed
Use it whenUsers search with both exact terms and meaning, and you want both in one query.
Trade-offMore concepts and configuration to learn than simpler stores; some advanced features need a license key.
At a glance
| Pinecone | Weaviate | |
|---|---|---|
| Used by | 55 makers' products · 23 open-source projects | 16 makers' products · 20 open-source projects |
| Cost at default usagevectors stored 1 million vectors, queries 1 million queries, vectors written or updated 500k writes | $113/mo Standard | $253/mo Flex |
| Downloads | 822.6k/wk−35% vs npm | 372.6k/wk−65% vs npm |
| Pricing | Free Starter tier; Builder $20/month flat, Standard usage-based with a $50/month minimum, plus an Enterprise tier. · paid from $20/mo | Core engine free to self-host (BSD-3-Clause); Weaviate Cloud has an always-free tier and pay-as-you-go plans from $45/month; some advanced features require a license key. · paid from $45/mo |
| Free tier | Yes | Yes |
| Open source | No | Yes · self-hostable |
| Incidents, 90 daysfrom its status page | 9 (6 major) | no public status feed |
Cost as you grow
Both cost $0 up to 100k vectors; from 500k vectors Pinecone costs less ($20 vs $126); from about 5M vectors Weaviate does ($1,263 vs $2,532). They're different kinds of tool — managed vector store and open-source vector store — so the prices don't buy the same thing.
The numbers, plan by plan
| Vectors stored (1,536 dimensions, about 6 GB per million) | Pinecone | Weaviate |
|---|---|---|
| 0.1 | $0 Starter | $0 Free |
| 0.5 | $20 Builder | $126 Flex |
| 1 | $113 Standard | $253 Flex |
| 5 | $2,532 Standard | $1,263 Flex |
| 10 | $9,987 Standard | $2,526 Flex |
| 50 | $246,797 Standard | $12,629 Flex |
| 100 | $985,753 Standard | $25,259 Flex |
What makers say
Makers on using it for vector database, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.
On PineconeTwelveLabs uses Pinecone to efficiently store and search the vector embeddings produced by our embedding model, enabling fast, scalable retrieval across large video and text datasets.
Though we are using function tools to retrieve information from our integrations in real-time, we also use Pinecone to retrieve relevant long-term information.
We needed a vector database that's fast, reliable, and serverless for our RAG system. Pinecone was the easiest to set up and performs consistently at scale.
On WeaviateTo store all our vector embeddings, now a staple for us to build forward. Their automatic 'load balancing' on which vectors are recently used is a game changer for system optimization
Unbody is built on top of Weaviate, making Unbody content API run 100% on a vector database. Weaviate modular architecture as well as user-friendly GraphQl API has played a vital role in our product.
Weaviate gives us fast, semantic search across unstructured call data, crucial for surfacing insights in real time. Its native vector support and scalability made it the best fit for building an AI native platform like Insight7.
Loved and watch-outs
Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.
PineconeMost loved
Watch-outs
On Product Hunt: 4.9★, 74 reviews · mentioned most: ease of use, scalability, high-performance vector database- It is one more database to run and sync, when Postgres or plain search often covers the need. HNHN 2HN 3HN 4
- Its core features have become a commodity, and it was late to integrated embeddings compared with rivals. HNHN 2HN 3HN 4
- It stores embeddings without the source chunk, unlike most other vector databases. HN
WeaviateMost loved
- Open source and free to run, with good docs and an active, friendly community. HNweaviate.ioPHHN 2
- Scales to production workloads, including multi-tenant setups on its managed cloud. weaviate.ioPHPH 2weaviate.io 2
- Built-in vectorization and a GraphQL API let queries mix semantic search with structured data. PHHNHN 2
Watch-outs
On Product Hunt: 4.9★, 13 reviews · mentioned most: vector embeddingsWho uses each
Pinecone55 makers' products
ClueoChat
Handit.ai
KuseWeaviate16 makers' products
Depth
Zefi.aiWhat makers pair each with
With PineconeLLM API
Pinecone + OpenAI API:
AI Context Flow
Brev.io
CustomGPT
Human Behavior
Kick
Kipps AI
Lookie AI
ManyPI
Nerve
Officely AI
omi
OneNodeand 7 more
AI Context FlowBrev.ioCustomGPTHuman BehaviorKickKipps AILookie AIManyPINerveOfficely AIomiOneNodeand 7 more
Magic Patterns
Nia
Outlit AI
Toffu AI
Youkti
Help Scout
TometoFrontend Framework
Mnemosphere AI
NBot
Swytchcode
Velpha
Pod AIWith WeaviateTransactional Email
Weaviate + Postmark:
Lamatic.ai
Lamatic.aiLLM API
Weaviate + OpenAI API:
cognee
Cortex
Insight7
Quantera.ai
cogneeCortexInsight7Quantera.aiNeither quite right?
See the whole vector database decision →
pgvectorInside your databaseApps already on Postgres that want vector search in the same database, joined with normal tables.
ChromaEmbedded / local-firstPrototyping RAG on your laptop with a pip or npm install and no server to run.vs Pinecone →
QdrantOpen-source vector storeHeavy metadata filtering alongside vector search, self-hosted from one binary or on its managed cloud.vs Pinecone →vs Weaviate →
turbopufferManaged vector storeVery large or many-tenant indexes where storing everything on object storage keeps cost down.vs Pinecone →