Pinecone

What is Pinecone?

Pinecone is a fully managed vector database that developers use to store embeddings and run semantic, full-text and hybrid search for AI applications. Its serverless indexes are metered on read units, write units, storage and egress, and the platform also offers Pinecone Inference for embedding and reranking models and Pinecone Assistant for building retrieval-augmented chat over uploaded files. Teams pick a cloud and region on paid plans, add Dedicated Read Nodes for predictable performance, and use namespaces to separate data by tenant or category. Typical projects are semantic search over a knowledge base, recommendation engines and forum answering bots built on RAG. Pinecone pricing starts with a free Starter plan, followed by Builder at $20 a month flat, Standard with a $50 monthly minimum and a 3-week trial that includes $300 in credits, and Enterprise with a $500 monthly minimum. Usage above the minimum on Standard and Enterprise is billed pay-as-you-go.

Use cases

• Build semantic search over documents
• Power RAG chatbots
• Create recommendation engines
• Run hybrid dense and sparse search
• Store embeddings at scale
• Rerank search results
• Answer questions over uploaded files

Who it's for

• AI and ML engineers
• Backend developers
• Startups building AI apps
• Enterprise platform teams

Why use Pinecone

• Fully managed infrastructure means no servers or index tuning to run for vector search.
• A free Starter tier lets you prototype search and RAG apps before spending anything.
• Embedding, reranking and file-based assistants sit next to the database under the same API and billing.
• Cost is metered per read, write, storage and egress, so small workloads stay inexpensive and large ones scale with usage.
• Enterprise options such as BYOC, private endpoints and customer managed keys help with security reviews.

Pinecone features

• Serverless vector indexes (dense, sparse and full-text)
• Namespaces for splitting data inside an index
• Pinecone Inference for embedding and reranking models
• Pinecone Assistant for chat over uploaded files
• Dedicated Read Nodes
• Import from object storage
• Backup and restore
• Prometheus and Datadog monitoring
• RBAC and SAML 2.0 SSO
• Bring Your Own Cloud with private endpoints
• Customer managed encryption keys and audit logs on Enterprise

Pinecone integrations

• AWS
• Microsoft Azure
• Prometheus
• Datadog
• AWS PrivateLink
• Discord

How to get started with Pinecone

1. Create a Pinecone account and start on the free Starter plan.
2. Create an index and choose dense, sparse or full-text search, plus a cloud and region on paid plans.
3. Embed your data, using Pinecone Inference or your own model, and upsert records into namespaces.
4. Query the index with semantic, full-text or hybrid search and optionally rerank the results.
5. Monitor usage in the console and move to Builder, Standard or Enterprise as limits or requirements grow.

Pinecone limitations

• Starter is limited to AWS in us-east-1, up to 5 indexes, 2 GB of storage, 2M write units and 1M read units per month
• Builder blocks usage beyond its limits rather than billing it
• Reranking on Starter and Builder is limited to bge-reranker-v2-m3
• Standard and Enterprise charge a monthly minimum of $50 and $500 respectively
• HIPAA is an add-on on Standard and included from Enterprise

Pinecone pricing

Yes, Pinecone has a free plan. Paid plans start at $20 per month, according to the official pricing page on 24 Oct 2026.

Pinecone plans

• Starter

  Free

  • Pinecone Database On-Demand
  • Pinecone Inference
  • Pinecone Assistant
  • Dense, sparse and full-text indexes
  • Community support via Discord

• Builder

  $20/month flat

  • Everything in Starter
  • Increased usage limits
  • Choose your cloud and region
  • Prometheus and Datadog monitoring

• Standard

  $50/month min. usage

  pay as you go above the minimum

  • Everything in Builder
  • Dedicated Read Nodes
  • Backup and restore
  • RBAC and SSO (SAML 2.0)
  • 3 week trial with $300 credits

• Enterprise

  $500/month min. usage

  pay as you go above the minimum

  • Everything in Standard
  • 99.95% uptime SLA
  • Bring Your Own Cloud (BYOC)
  • Private endpoints
  • Audit logs and SCIM
  • Pro support included

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

Pinecone alternatives

The main Pinecone alternatives listed on Debuly are Weaviate, Qdrant, Chroma, Zilliz Cloud, Baseplate and Octen. The table compares pricing and platforms; order is A–Z.

1. Ba

   Baseplate

   Backend for LLM apps: a hybrid database for data and embeddings, search, an app builder and API endpoints

   Developer platformsAutomation and agents
   FreemiumVisit Baseplate (official site)
2. 

   Chroma

   Open-source search database for AI apps, with vector, full-text, regex and metadata search and a serverless cloud option.

   Developer platformsResearch and searchAutomation and agents
   Open sourceVisit Chroma (official site)
3. 

   Octen

   Real-time web search API for AI agents and LLM apps, with extraction, embeddings, deep research and pay-as-you-go pricing.

   Developer platformsResearch and searchAutomation and agents
   FreemiumVisit Octen (official site)
4. 

   Qdrant

   An open-source vector database and search engine for AI workloads, available self-hosted or as Qdrant Cloud with a free tier.

   Developer platformsResearch and searchAutomation and agents
   FreemiumVisit Qdrant (official site)
5. 

   Weaviate

   Open-source vector database with hybrid search and a managed Weaviate Cloud for semantic search, RAG and recommendations.

   Developer platformsResearch and search
   FreemiumVisit Weaviate (official site)
6. 

   Zilliz Cloud

   Fully managed vector database from the team behind Milvus, with free, serverless and dedicated clusters plus on-demand lake-scale compute.

   Developer platformsResearch and search
   FreemiumVisit Zilliz Cloud (official site)

Pinecone FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from pinecone.io · fetched 24 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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