# cocoindex-io/cocoindex

Incremental engine for long horizon agents 🌟 Star if you like it!

Repository: https://github.com/cocoindex-io/cocoindex
Canonical: https://ross.abutalabs.com/products/cocoindex
Homepage: https://cocoindex.io
Language: Rust
License: Apache-2.0
License Family: permissive
Topics: ai, change-data-capture, data-indexing, etl, indexing, python, rag, real-time, rust, semantic-search, data-engineering, data-processing, help-wanted, knowledge-graph, llm, context-engineering, agentic-data-framework, long-horizon-agent, ai-agents, codebase-intelligence
Last push: 2026-08-26T18:07:48+00:00

## Health v2 (maintenance only)
Score: 82/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 85, longevity 39
- inputs: {"age_days": 548, "days_push": 7, "days_rel": 21, "gap_med": 2.0, "n_releases_24m": 165}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 11409, forks 888 (observed 2026-08-28T04:10:46.941463+00:00)

## What it is
CocoIndex is an open-source incremental data framework for AI, with a Rust engine and a declarative Python API that keeps sources (files, S3, Postgres, Kafka, etc.) in sync with targets like pgvector, Qdrant, Neo4j, and LanceDB by reprocessing only the delta. It is aimed at building continuously fresh context for AI agents, including RAG pipelines, semantic search, knowledge graphs, and real-time codebase indexing.

## Use cases
- build a rag pipeline over my documents
- keep a vector index of my codebase in sync with every commit
- incrementally embed files into postgres pgvector
- build a knowledge graph from meeting notes or docs
- semantic search over pdfs and markdown
- feed fresh context to coding and code-review agents
- stream csv or kafka data into a vector database
- index code call graphs and symbols for an ai agent

## When to choose
- you need continuously updated indexes where reprocessing everything on each change is too slow or expensive
- you want a declarative python flow from sources like s3, postgres, or local files to vector stores or graph databases
- you are building ai agents that need fresh retrieval context, including codebase intelligence
- you want incremental etl with built-in connectors and only-delta processing

## When to avoid
- you need a one-off batch etl job with no ongoing sync
- your pipeline is simple enough that a plain script or existing etl tool suffices
- you need a target store or source not covered by its connectors and don't want to write a custom connector
- you require a mature v1 ecosystem — the v0 docs are already in maintenance mode

## Facets
- artifact type: framework
- maturity: active
- function: etl, rag, vector-database, search-engine, data-science, llm-inference, agent-framework, streaming, workflow-automation
- domain: large-language-models, databases, developer-tools
- platform: python, rust, cross-platform, self-hosted
- tags: incremental-processing, change-data-capture, semantic-search, knowledge-graph, vector-embeddings, codebase-indexing, declarative-pipelines, context-engineering, live-indexing, pgvector, data-engineering, retrieval-augmented-generation, ai-agents, search, docker

## Member repositories
- cocoindex-io/cocoindex (main) score 82

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:46.941463+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:15:36.989753+00:00, confidence not recorded.
  - readme: https://github.com/cocoindex-io/cocoindex (fetched 2026-08-28T04:10:46.941463+00:00, sha eda87322291c)
  - homepage: https://cocoindex.io (fetched 2026-08-29T08:14:28.964087+00:00, sha c3b3928c877f)
  - site_page: https://cocoindex.io/docs/examples (fetched 2026-08-29T08:14:28.966986+00:00, sha c95ff0fc23f9)
  - site_page: https://cocoindex.io/docs (fetched 2026-08-29T08:14:28.969100+00:00, sha a3d563df45a3)
  - site_page: https://cocoindex.io/docs/programming_guide/core_concepts (fetched 2026-08-29T08:14:28.970917+00:00, sha ba56805493d9)
  - site_page: https://cocoindex.io/docs-v0 (fetched 2026-08-29T08:14:28.973281+00:00, sha 27f48afeda26)
- Data as of 2026-08-30T08:39:29.467469+00:00.