> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Pinecone Database

> Pinecone Database is the retrieval foundation of Pinecone's trusted AI knowledge platform, bringing full-text and semantic search into one managed database.

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Pinecone Database powers retrieval for AI agents and applications, including search, recommendations, and long-term memory. Each index has a schema that declares the fields you need, such as full-text-search fields, dense vectors, and sparse vectors, so one index can serve whichever retrieval approach a query calls for.

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/guides/get-started/quickstart">
    Pick a search path and run your first search in minutes
  </Card>

  <Card title="Key terms" icon="book" href="/guides/core-concepts/key-terms">
    Organizations, projects, indexes, namespaces, documents, and records
  </Card>

  <Card title="Data modeling" icon="table" href="/guides/index-data/data-modeling">
    Design the fields your index needs for the searches you'll run
  </Card>

  <Card title="Search overview" icon="magnifying-glass" href="/guides/search/search-overview">
    Compare search types and choose the right approach for each query
  </Card>

  <Card title="IDEs & CLIs" icon="wand-magic-sparkles" href="/integrations/ai-coding-tools">
    Use Pinecone with Claude Code, Codex, Gemini CLI, Cursor, and other agentic tools
  </Card>

  <Card title="MCP server" icon="server" href="/guides/operations/mcp-server">
    Connect any MCP-compatible agent to Pinecone for search and index management
  </Card>
</CardGroup>

## What you can do

With Pinecone Database, you can:

* Serve [full-text search](/guides/search/full-text-search), [semantic search](/guides/search/semantic-search), [sparse-vector search](/guides/search/lexical-search), and [hybrid search](/guides/search/hybrid-search) from one index. To choose an approach, see [Search overview](/guides/search/search-overview).
* Upsert and query with text instead of vectors. With [integrated embedding](/guides/index-data/indexing-overview#integrated-embedding), Pinecone generates the vectors from your text server-side.
* Narrow results with [metadata filters](/guides/search/filter-by-metadata), then [rerank](/guides/search/rerank-results) them for relevance.
* Keep each tenant's data separate within one index by using [namespaces](/guides/index-data/implement-multitenancy).
* Scale reads for sustained, high query volumes with [dedicated read nodes](/guides/index-data/dedicated-read-nodes/overview).
* Run in production by [backing up](/guides/manage-data/backups-overview) your indexes and deploying in your own cloud account with [Bring Your Own Cloud (BYOC)](/guides/production/bring-your-own-cloud).

## Resources

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  <Card title="API reference" icon="code-simple" href="/reference">
    Details about the Pinecone APIs, SDKs, and architecture
  </Card>

  <Card title="Examples" icon="grid-round" iconType="solid" href="/examples">
    Notebooks and sample apps with common AI patterns
  </Card>

  <Card title="Models" icon="cube" href="/models/overview">
    Embedding and reranking models hosted by Pinecone
  </Card>

  <Card title="Integrations" icon="link-simple" href="/integrations/overview">
    Third-party integrations for LangChain, LlamaIndex, and more
  </Card>

  <Card title="Troubleshooting" icon="screwdriver-wrench" href="/troubleshooting/contact-support">
    Common errors, account help, and how to contact support
  </Card>

  <Card title="Changelog" icon="party-horn" href="/release-notes">
    What's new in Pinecone
  </Card>
</CardGroup>

## Other Pinecone products

<CardGroup cols={2}>
  <Card title="Pinecone Assistant" icon="comments" href="/guides/assistant/overview">
    A managed service for RAG chat and agent applications grounded in your data
  </Card>

  <Card title="Pinecone Nexus" icon="brain-circuit" href="/guides/nexus/overview">
    The knowledge engine for agents, serving grounded, cited answers in one call
  </Card>
</CardGroup>