Pinecone

Pinecone is a fully managed serverless vector database that stores and searches embeddings so AI applications can retrieve semantically relevant context from billions of records in milliseconds. It is aimed at engineering teams building retrieval-augmented generation, agents, search and recommendation systems who do not want to run, shard and tune their own vector index in production.

Pinecone is a fully managed vector database that stores, indexes and searches high-dimensional embeddings so applications can retrieve semantically similar records from billions of items in milliseconds. Its serverless architecture separates storage from compute and reads from writes, running on object storage with intelligent tiering, which lets a single index scale to millions of namespaces and billions of vectors without capacity planning or manual sharding; the vendor states updates become searchable within seconds and that customers pay only for the read and write operations they actually perform. Beyond dense vector search, Pinecone indexes support sparse retrieval and full-text keyword search (in public preview) for hybrid retrieval, alongside metadata filtering, namespaces and time-to-live for data lifecycle control. The platform bundles first-party inference — embedding, reranking and Pinecone's own sparse embedding models — so teams can run end-to-end retrieval without wiring a separate model provider into the pipeline, and adds Pinecone Assistant, a managed RAG and chat service with citation highlighting, plus Dedicated Read Nodes and a Bring Your Own Cloud deployment for isolated or regulated workloads. Founded in 2019 by Edo Liberty and headquartered in New York, the company has raised $138M from Andreessen Horowitz, ICONIQ, Menlo Ventures and Wing Venture Capital, and states on its site that over 9,000 customers use it. In September 2025 Liberty moved to Chief Scientist and Ash Ashutosh became CEO, a transition that followed reports Pinecone had held early talks with bankers about strategic options as every major database vendor began shipping built-in vector search.

Category

Infrastructure & Cloud

Pricing

Freemium, Usage-based, Subscription

Target Market

CTOs, Enterprise Developers, Data Scientists, Platform Engineers, ML Engineers

Deployment

Cloud-first, API-based, Multi-cloud, Hybrid

Founded

2019

Headquarters

New York, United States

Team Size

51-200

Customers

9,000+ (vendor-stated on pinecone.io; the September 2025 newsroom release cited 5,000+)

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  Serverless architecture

  Separates storage from compute and reads from writes on object storage, so capacity planning, sharding and index tuning disappear and cost tracks operations performed rather than provisioned nodes.

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  Hybrid dense, sparse and full-text search

  Combines vector similarity, sparse keyword retrieval and full-text search (public preview) in a single index, which lifts recall on queries containing exact identifiers, product codes or rare terms.

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  Built-in inference: embedding and reranking

  Hosts embedding and reranking models — including Pinecone's own sparse embedding models — inside the database, removing a separate model provider and a network round trip from the retrieval path.

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  Pinecone Assistant

  A managed RAG and chat service with citation highlighting that returns grounded answers over uploaded files, so teams get a working knowledge assistant without building an orchestration layer.

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  Namespaces, metadata filtering and TTL

  Scales to millions of namespaces for per-tenant isolation, filters on metadata for access control, and expires records automatically so stale documents stop surfacing in answers.

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  Dedicated Read Nodes and Bring Your Own Cloud

  Isolates high-availability query workloads on reserved capacity and can run inside the customer's own cloud account, which is what unlocks private endpoints and data-locality requirements.

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  MCP servers and framework integrations

  Ships Model Context Protocol servers plus LangChain, Haystack and n8n integrations, so agents and existing pipelines can query the index without bespoke glue code.

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  Enterprise knowledge assistant

  Index internal wikis, contracts and support tickets so employees get cited answers from current documents instead of searching several systems by hand.

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  Customer support deflection

  Retrieve the most relevant help articles and prior resolved tickets for an LLM to answer with, cutting first-response time and escalation volume.

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  Agent long-term memory

  Store conversation and task history as embeddings so an agent recalls prior context across sessions rather than restarting from an empty state each run.

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  Semantic product and catalogue search

  Match shopper intent to products by meaning rather than keyword overlap, with metadata filters enforcing stock, region and price constraints on every query.

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  Fraud, duplicate and anomaly detection

  Compare a new record against billions of historical embeddings in milliseconds to surface near-duplicates and outliers that rule-based checks miss.

List pricing is published in full. Four tiers — Starter free, Builder $20/mo flat, Standard from $50/mo and Enterprise from $500/mo — where the paid tiers are platform minimums plus pay-as-you-go consumption. Metering is by read units, write units and storage rather than seats: storage runs $0.33/GB/month, write units $4.00-$4.50 per million on Standard and $6.00-$6.75 on Enterprise, and read units $16-$18 per million on Standard against $24-$27 on Enterprise, with egress free to 100GB then $0.10/GB. Read units are the line that surprises teams, because a chatty RAG or agent workload issues far more reads than writes and the same Enterprise upgrade that buys the SLA also raises the per-unit rate by roughly 50%. Bring Your Own Cloud, private endpoints, customer-managed keys, audit logs and SCIM are Enterprise-only; HIPAA is a $190/mo add-on on Standard and bundled at Enterprise.

This page was written from 8 sources, 5 on domains other than pinecone.io.

1. 1.pinecone.io — pinecone.iovendor
2. 2.pinecone.io — pricingvendor
3. 3.pinecone.io — next chaptervendor
4. 4.security.pinecone.io — security.pinecone.io
5. 5.peerspot.com — pinecone reviews
6. 6.techtarget.com — Vector database vendor Pinecone eyes future under new CEO
7. 7.calcalistech.com — rz31q82b5
8. 8.github.com — pinecone io