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Pinecone vs Vespa

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Both have one
Public API
Both have one
Best fit
Pinecone: RAG and agent memory backends that need low-latency retrieval at scale · Vespa: Teams building large-scale search, recommendation or RAG systems that need hybrid ranking
Platforms
Pinecone: Web · Vespa: Linux, macOS
Trust score
About even — Pinecone 92, Vespa 93

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

PineconeManaged vector database for similarity search over billions of embeddings, with serverless and BYOC optionsVespaOpen-source search and vector engine that combines text, vectors, ranking and model inference for RAG, recommendations and agents.

Side by side

FactPineconeVespa
CategoryVector Databases & RAGVector Databases & RAG
Pricing modelFreemiumFreemium
Starts at$20/mo—
Public APIYesYes
Trust score92 / 10093 / 100
PlatformsWeb, APIAPI, Linux, macOS
CompanyPinecone Systems, Inc.Vespa.ai AS
Launched20212017
Last verifiedSep 6, 2026Oct 2, 2026

What our research says

Pinecone

The default managed choice when you want vector search without operating infrastructure, and serverless billing makes small projects cheap to start. Costs are metered per read/write unit, so query-heavy workloads need modeling up front - bills scale with success, and storage, egress and support are all separate lines.

Pros

  • Serverless architecture separates storage from compute
  • Free tier plus a $20 flat Builder plan lowers the entry cost
  • Hosted embedding and reranking models reduce pipeline glue
  • Enterprise controls: SSO, RBAC, audit logs, BYOC, HIPAA add-on

Cons

  • Unit-based pricing is hard to forecast for spiky query loads
  • Closed source, with BYOC reserved for the Enterprise tier
  • Responsive support costs $29-250/month extra on lower tiers

Vespa

Vespa is built for search and recommendation workloads where relevance, hybrid retrieval and low latency at scale matter more than a quick prototype. That depth makes it heavier to learn than a simple vector store, so it pays off mainly for production-grade retrieval.

Pros

  • Open source under Apache-2.0, with a managed Vespa Cloud option
  • Combines vector search, text search, tensors and model inference in one platform
  • Supports real-time updates alongside queries
  • Case studies include Perplexity, according to the vendor

Cons

  • Steeper learning curve than lightweight vector databases
  • Cloud rates are not shown as a plain price table, so cost estimation takes a trial or sales contact
  • Operating a self-hosted cluster is a real infrastructure commitment

Which one fits

Choose Pinecone if you need

  • RAG and agent memory backends that need low-latency retrieval at scale
  • Teams that would rather pay per usage than operate open-source vector stores
  • Enterprises needing SSO, RBAC, HIPAA or bring-your-own-cloud deployment

Choose Vespa if you need

  • Teams building large-scale search, recommendation or RAG systems that need hybrid ranking
  • Engineers who want one engine for text, vectors and structured filters
  • Organisations that want to start self-hosted and move to a managed cloud later

Pinecone vs Vespa: the questions people ask

Is Pinecone cheaper than Vespa?

Pinecone starts at $20/mo. Vespa has a free tier; what its paid plans cost is not confirmed by us yet.

Does Pinecone or Vespa have a free tier?

Both: Pinecone has a free tier, and Vespa has a free tier.

Which has a public API, Pinecone or Vespa?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

More comparisons

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