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 data—whether structured or unstructured—in real-time or interactive user environments.
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, Semantic UI should be more popular than FalkorDB. It has been mentiond 19 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 milliseconds—critical for real-time AI interactions. - Source: dev.to / about 2 months 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 / about 2 months ago
For AI architects, integrating graph-native storage with LLMs isn’t optional—it’s imperative for building systems capable of robust, multi-hop reasoning at scale. - Source: dev.to / 2 months ago
Semantic UI: A fully semantic front-end development framework. - Source: dev.to / 7 months ago
Semantic UI[1] was one I used to use, both the plain CSS one as well as the React version of the library. Version 3.0 is coming (eventually), which has left it a bit outdated for a while, but it's still a solid UI library imho. I have been switching away to Tailwind. [1]: https://semantic-ui.com/. - Source: Hacker News / 10 months ago
What stack are you using? I personally recommend utilizing readily available components: https://ui.shadcn.com/ https://mui.com/ https://semantic-ui.com/ etc.. - Source: Hacker News / over 1 year ago
Are you cool with JS frameworks? If so, you can use a higher level of abstraction that takes care of the CSS for you. If you just want to mock something up, you can use a pre-built UI system / component framework and just put together UIs declaratively, without having to worry about the underlying CSS or HTML at all. Examples include https://mui.com/ and https://chakra-ui.com/ and https://ant.design/ Really easy... - Source: Hacker News / over 1 year ago
Honestly you should build a webpage and use a UI library if you want markdown with some extra pop. Check out semantic ui. Source: over 2 years ago
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
Bootstrap - Simple and flexible HTML, CSS, and JS for popular UI components and interactions
Memgraph - Memgraph is an open source graph database built for real-time streaming and compatible with Neo4j. Whether you're a developer or a data scientist with interconnected data, Memgraph will get you the immediate actionable insights fast.
Materialize CSS - A modern responsive front-end framework based on Material Design
TigerGraph DB - Application and Data, Data Stores, and Graph Database as a Service
UIKit - A lightweight and modular front-end framework for developing fast and powerful web interfaces