cocoindex-io/cocoindex
Incremental engine for long horizon agents 🌟 Star if you like it!
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest 6 days ago, with 100 contributors on GitHub.
Peaked at #9 in the weekly ranking the week of Dec 14, its best in the past year.
Use Cases & Benefits
- Provides an ultra performant incremental data transformation engine for AI workflows with a Rust core and Python interface.
- Enables minimal recomputation and automatic data lineage for efficient, real-time synchronization between source data and targets.
- Use for building semantic search indexes by transforming and embedding text documents incrementally.
- Use for creating knowledge graphs from unstructured documents with automated relationship extraction and dataflow programming.
- Use for integrating AI-powered data pipelines that require incremental ETL and vector indexing across diverse storage backends.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Ultra performant data transformation framework for AI, with core engine written in Rust. Support incremental processing and data lineage out-of-box. Exceptional developer velocity. Production-ready at day 0.
⭐ Drop a star to help us grow!
CocoIndex makes it effortless to transform data with AI, and keep source data and target in sync. Whether you’re building a vector index for RAG, creating knowledge graphs, or performing any custom data transformations — goes beyond SQL.
Just declare transformation in dataflow with ~100 lines of python
CocoIndex follows the idea of Dataflow programming model. Each transformation creates a new field solely based on input fields, without hidden states and value mutation. All data before/after each transformation is observable, with lineage out of the box.
Particularly, developers don't explicitly mutate data by creating, updating and deleting. They just need to define transformation/formula for a set of source data.
Native builtins for different source, targets and transformations. Standardize interface, make it 1-line code switch between different components - as easy as assembling building blocks.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+637 stars over 90 days across 13 snapshot days; best day +39 on Aug 12.
Forks
922+61
Open issues
113+47
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Leonxlnx/taste-skill | 110.7K | +5.2K | 55 | 1 day ago |
| calesthio/OpenMontage | 77.2K | +4.2K | 40 | — |
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| cocoindex-io/cocoindex | 11.8K | — | 65 | 6 days ago |
| Category median | 98.1K | +5.2K | 45 | — |
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