FalkorDB
neo4j
ArangoDB
Amazon Neptune
RedisGraph
TigerGraph DB
Dgraph
Titan Database
Commit Together by Github
Refined GitHub
GitHub for Mobile
GitHub for Atom
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GitStreak
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Commit Club
FalkorDB delivers an accurate, multi-tenant RAG solution powered by a low-latency, scalable graph database technology. Our solution is purpose-built for development teams working with complex, interconnected dataโwhether structured or unstructuredโin real-time or interactive user environments.
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FalkorDB's answer
C, Rust, Next.js
FalkorDB's answer
An ultra-low latency Graph Database
FalkorDB's answer
x100 faster than the leading solutions
FalkorDB's answer
Developers, Architects, Data scientists, CTOs
FalkorDB's answer
An ultra-low latency Graph Database that perfects the Knowledge Graph for KG-RAG. Effectively overcoming the existing limitations of RAG for Large Language Models (LLM).
FalkorDB is the first queryable Property Graph database to use sparse matrices to represent the adjacency matrix in graphs and linear algebra to query the graph.
Based on our record, FalkorDB should be more popular than Commit Together by Github. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Use a low-latency graph database: Integrate FalkorDB for its sparse matrix representation and optimized linear algebra-based traversals. Queries execute in millisecondsโcritical for real-time AI interactions. - Source: dev.to / over 1 year ago
In vector databases, data is stored as high-dimensional vector embeddings, which are numerical representations generated by machine learning models to capture the features of data. When querying, the input is converted into a vector embedding, and similarity searches are performed between the query vector and stored embeddings using distance metrics like cosine similarity or Euclidean distance to retrieve the most... - Source: dev.to / over 1 year ago
For AI architects, integrating graph-native storage with LLMs isnโt optionalโitโs imperative for building systems capable of robust, multi-hop reasoning at scale. - Source: dev.to / over 1 year ago
There is "Co-authored-by" which is supported on GitHub [1] and seems appropriate if the maintainer is basing the solution on someone's code. [1] https://github.blog/2018-01-29-commit-together-with-co-authors/. - Source: Hacker News / over 4 years ago
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GitHub for Mobile - The worldโs development platform, in your pocket
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GitHub for Atom - Git and GitHub integration right inside Atom