raphaelmansuy/edgequake
EdegQuake 🌋 High-performance GraphRAG inspired from LightRag written in Rust; Transform documents into intelligent knowledge graphs for superior retrieval and generation observed · 2026-08-28
Health v2 · maintenance only
79/100
- Activity 99
- Release rhythm 87
- Longevity 18
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 0.0
- age_days: 255
- days_rel: 8
- days_push: 8
- n_releases_24m: 75
Adoption not part of the score
2078 stars · 243 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
EdgeQuake is a high-performance Graph-RAG framework written in Rust, inspired by LightRAG, that transforms documents (PDFs, markdown, text) into knowledge graphs for retrieval-augmented generation. It ships as a full self-hosted stack with a REST API, Web UI, PostgreSQL-backed graph (AGE) and vector (pgvector) storage, and six retrieval modes.
Use cases
- build a graphrag pipeline over my pdf documents
- extract entities into a knowledge graph for better rag answers
- self-host a lightrag alternative without python
- query documents with hybrid vector and graph retrieval
- run multi-tenant rag with source traceability
- integrate a graph-based retriever into langchain or open webui
- ingest multi-column pdfs into a searchable knowledge base
When to choose
- you want Graph-RAG quality with Rust performance instead of Python pipeline fragility
- you need entity relationships, lineage, and provenance in retrieval results
- you want self-hosting with PostgreSQL, pgvector, and Apache AGE
- you need multi-tenancy, ingestion cancellation, and production operational features
- you prefer Docker quickstart deployment with OpenAI or Ollama providers
When to avoid
- you only need simple vector similarity search without graph structure
- you cannot run PostgreSQL or Docker in your environment
- you need a lightweight embedded library rather than a full service stack
- your team depends on a mature ecosystem with long-term stability guarantees
- you want a fully managed cloud service
Facets
service · maturity active
rag search-engine vector-database nlp machine-learning pdf api-framework http-server large-language-models artificial-intelligence pdf self-hosted rust self-hosted windows cross-platform graphrag knowledge-graph lightrag-inspired entity-extraction pgvector postgresql-age hybrid-retrieval multi-tenancy pdf-ingestion openai ollama langchain-integration open-webui retrieval-augmented-generation search natural-language-processing docker web-server linux macos
9 sources
- readme: https://github.com/raphaelmansuy/edgequake · fetched 2026-08-28 · 314304179076
- homepage: https://edgequake.com · fetched 2026-08-29 · a98387930485
- site_page: https://edgequake.com/docs · fetched 2026-08-29 · 14e992364753
- site_page: https://edgequake.com/docs/getting-started · fetched 2026-08-29 · 2ec7f14c439b
- site_page: https://edgequake.com/docs/concepts · fetched 2026-08-29 · e1a3c048741b
- site_page: https://edgequake.com/docs/deep-dives · fetched 2026-08-29 · 0c2a1440dace
- site_page: https://edgequake.com/docs/operations · fetched 2026-08-29 · b6ca49160797
- site_page: https://edgequake.com/docs/integrations · fetched 2026-08-29 · 85d5a9cb37f8
- site_page: https://edgequake.com/docs/api-reference · fetched 2026-08-29 · 8651b2807342
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| raphaelmansuy/edgequake | main | 79 |
For agents
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Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem