# Infino

> Infino is an open-source retrieval engine for full-text, vector, and SQL search, with your data stored as Apache Parquet on object storage.

- [Infino: open-source retrieval engine for AI apps](https://infino.ai/docs/index.md): Infino is an open-source retrieval engine for full-text, vector, and SQL search, with your data stored as Apache Parquet on object storage.
- [Quickstart: install Infino and run your first search](https://infino.ai/docs/quickstart.md): Install Infino, then index a small knowledge base and retrieve over it four ways (BM25, vector, hybrid, and SQL) in Python, Node.js, or Rust.
- [Core concepts: how Infino indexes and queries Parquet](https://infino.ai/docs/core-concepts.md): How Infino works. One copy of your data as Apache Parquet with built-in search indexes, queryable four ways (full-text, vector, SQL, hybrid) in-process.
- [Connect & storage: memory, disk, S3, and Azure](https://infino.ai/docs/guides/storage.md): Run Infino against in-memory, local disk, or object storage backends like S3 and Azure Blob, picked at runtime by the connect URI scheme.
- [Tables: schemas, rows, updates, and compaction](https://infino.ai/docs/guides/tables.md): Manage Infino tables. Define schemas, append rows, update and delete by predicate, compact Parquet files, reclaim storage, and inspect the table catalog.
- [Embeddings: bring your own vectors to Infino](https://infino.ai/docs/guides/embeddings.md): Bring your own embeddings to Infino. Supply vectors from any model, store them alongside your data, and index them for fast kNN vector search.
- [Indexing: BM25 full-text and IVF vector indexes](https://infino.ai/docs/guides/indexing.md): Declare full-text BM25 and vector IVF indexes on your Infino tables, and pick the dimension and distance metric that match your embeddings.
- [Search: BM25, vector, hybrid, and SQL retrieval](https://infino.ai/docs/guides/search.md): Search Infino five ways from one table, BM25 full-text, vector kNN, hybrid, exact lookups, and SQL, and pick the right mode for your retrieval workload.
- [Parquet interop: read Infino tables with DuckDB and pandas](https://infino.ai/docs/guides/parquet-interop.md): Infino stores your data as standard Apache Parquet, so you can read tables directly from DuckDB, pandas, or pyarrow with no export step and no Infino runtime.
- [Infino Cloud](https://infino.ai/docs/cloud/index.md): Infino Cloud is the Infino retrieval engine served as a fully-managed, object-storage-native hosted service. No servers to run or size, usage-based, same API as the open-source engine.
- [Quickstart](https://infino.ai/docs/cloud/quickstart.md): Run the same Infino retrieval API against Infino Cloud, the hosted service. Only the connect target changes; every table and search call stays the same.
- [Authentication](https://infino.ai/docs/cloud/authentication.md): How Infino Cloud authenticates requests — API keys, the INFINO_API_KEY environment variable, the Authorization Bearer header, the https requirement, and key rotation.
- [Architecture](https://infino.ai/docs/cloud/architecture.md): How Infino Cloud is structured at a high level — a control plane, a serving layer, and object storage holding your data as Parquet, separating control, compute, and storage.
- [Errors & retries](https://infino.ai/docs/cloud/errors.md): Infino Cloud starts databases on demand, so the first request to an idle or brand-new database can briefly return a transient 503. Learn which errors clear on a retry and how to handle them.
- [Limits](https://infino.ai/docs/cloud/limits.md): Request-size limits on Infino Cloud, what happens when you exceed them, and how to size append batches.
- [FAQ](https://infino.ai/docs/cloud/faq.md): Frequently asked questions about Infino Cloud — how it differs from the open-source engine, where data lives, durability, data isolation, Parquet access, and API keys.
- [SQL reference for Infino queries and search functions](https://infino.ai/docs/sql-reference.md): Query Infino with SQL via query_sql, covering the supported dialect, the bm25_search, vector_search, and hybrid_search table functions, and how to compose them.
- [Infino FAQ: servers, durability, search, and embeddings](https://infino.ai/docs/faq.md): Operational and usage answers for evaluating and building on Infino, covering servers, durability, concurrency, embeddings, search, languages, and more.
- [Infino tradeoffs: where it fits and where it doesn't](https://infino.ai/docs/tradeoffs.md): What Infino optimizes for and what it doesn't, an honest look at where this retrieval engine fits your workload and where another tool is a better choice.
- [Troubleshooting common Infino errors and fixes](https://infino.ai/docs/troubleshooting.md): Common Infino errors and their fixes, covering in-memory update limits, schema and vector dimension mismatches, SQL query syntax, and language-specific gotchas.
- [Integrations with LangChain, AI SDK, CrewAI, and MCP](https://infino.ai/docs/integrations/index.md): Plug Infino retrieval into your stack with official integrations for LangChain, the Vercel AI SDK, CrewAI, and the Model Context Protocol (MCP).
- [LangChain integration with Infino VectorStore](https://infino.ai/docs/integrations/langchain.md): Use Infino as a LangChain VectorStore for vector, BM25 full-text, hybrid, and SQL retrieval in your Python and JavaScript LangChain applications.
- [Vercel AI SDK: build a retrieval-tool agent on Infino](https://infino.ai/docs/integrations/ai-sdk.md): Build a TypeScript knowledge-base agent with the Vercel AI SDK and Infino. Wire up tools for vector, BM25, and hybrid retrieval over your data.
- [CrewAI + Infino: retrieval tools for your agent crew](https://infino.ai/docs/integrations/crewai.md): Give CrewAI agents retrieval over your own data with Infino, exposing BM25, vector, hybrid, and SQL search as tools your crew can call during tasks.
- [Infino MCP server: retrieval for Claude, Cursor, and more](https://infino.ai/docs/integrations/mcp.md): Expose Infino retrieval (keyword, vector, hybrid, and SQL) to any Model Context Protocol client — Claude Code, Claude Desktop, Cursor, VS Code — over a local catalog, your own bucket, or Infino Cloud.
- [Infino tutorials: RAG, agent memory, hybrid search](https://infino.ai/docs/tutorials/index.md): Runnable, end-to-end Infino tutorials covering RAG pipelines, agent memory, hybrid search, code search, analytics over Parquet, and more examples.
- [Use cases: agent memory and retrieval with Infino](https://infino.ai/docs/use-cases/index.md): End products built on Infino, starting with agent memory, a ready-made OpenClaw plugin. Runnable RAG and hybrid-search examples live in the tutorials.
- [Agent memory: long-term recall for AI agents](https://infino.ai/docs/use-cases/agent-memory.md): Give AI agents long-term memory with Infino. Hybrid BM25 and vector recall over past conversations, ready-made as the memory-infino OpenClaw plugin.
- [Demos](https://infino.ai/docs/demos/index.md): Live demos built on Infino. Try the retrieval engine in your browser without installing anything, starting with Lantern, which answers questions about any public GitHub repo.
- [Lantern](https://infino.ai/docs/demos/lantern.md): Ask any public GitHub repo questions in plain English. Answers come from Infino search, with sources you can click.
- [Overview](https://infino.ai/docs/api-reference/index.md): API reference for the Infino SDKs — Rust, Python, and Node.js. The same client connects to a local store or to Infino Cloud; only the connect target changes. For the HTTP API, see the REST API section (Infino Cloud).
- [Local vs Infino Cloud](https://infino.ai/docs/api-reference/parity.md): Which operations are available on a local Infino connection versus Infino Cloud, and where behavior differs.
- [Infino CLI: create tables, ingest, and search](https://infino.ai/docs/cli.md): The infino command-line interface — create tables, ingest data, and run BM25, vector, and SQL search from your terminal or a coding agent.
- [Append rows](https://infino.ai/docs/api-reference/rows/append-rows.md): Append rows to a table. The body is an Arrow IPC stream, or a JSON `{"data": [...]}` envelope.
- [Delete rows](https://infino.ai/docs/api-reference/rows/delete-rows.md): Delete rows matching a predicate. `table` and `predicate` are query parameters; no body.
- [Update rows](https://infino.ai/docs/api-reference/rows/update-rows.md): Replace rows matching a predicate. `table` and `predicate` are query parameters; the body carries the replacement rows (Arrow IPC or JSON).
- [BM25 full-text search](https://infino.ai/docs/api-reference/search/bm25-full-text-search.md): Ranked BM25 full-text search over a full-text-indexed column.
- [Count matches](https://infino.ai/docs/api-reference/search/count-matches.md): Count the rows matching a full-text query.
- [Exact match](https://infino.ai/docs/api-reference/search/exact-match.md): Exact-value match over a column.
- [Hybrid search](https://infino.ai/docs/api-reference/search/hybrid-search.md): Hybrid BM25 and vector search, fused with reciprocal-rank fusion.
- [Run a SQL query](https://infino.ai/docs/api-reference/search/run-a-sql-query.md): Run a read-only SQL query across the database's tables.
- [Token match](https://infino.ai/docs/api-reference/search/token-match.md): Unranked token match over a full-text-indexed column.
- [Vector search](https://infino.ai/docs/api-reference/search/vector-search.md): Vector (kNN) search over a vector column, with an optional full-text pre-filter.
- [Create a table](https://infino.ai/docs/api-reference/tables/create-a-table.md): Create a table with an Arrow schema and optional full-text and vector indexes.
- [Drop a table](https://infino.ai/docs/api-reference/tables/drop-a-table.md): Drop a table from the database.
- [List tables](https://infino.ai/docs/api-reference/tables/list-tables.md): List the tables in the database.
- [Describe a table's schema](https://infino.ai/docs/api-reference/tables/describe-a-tables-schema.md): Return a table's column schema.
- [List databases](https://infino.ai/docs/api-reference/databases/list-databases.md): List your account's databases and their state.
- [Create a database](https://infino.ai/docs/api-reference/databases/create-a-database.md): Register a new database for your account.
- [Delete a database](https://infino.ai/docs/api-reference/databases/delete-a-database.md): Begin deleting a database. Idempotent.
- [Verify a storage binding](https://infino.ai/docs/api-reference/databases/verify-a-storage-binding.md): Prove the database's bring-your-own-bucket grant end to end; workers start only after this passes.

## OpenAPI Specs

- [openapi](/docs/api-reference/openapi.json)