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Update index.md
I've updated the docs index (homepage) 1. grammar 2. graph/graphrag paths 3. banner 4. about us
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description: "The fastest way to your knowledge"
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permalink: /
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---
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[![Docker Hub](https://img.shields.io/docker/pulls/falkordb/falkordb?label=Docker)](https://hub.docker.com/r/falkordb/falkordb/)
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[![Discord](https://img.shields.io/discord/1146782921294884966?style=flat-square)](https://discord.gg/ErBEqN9E) [![Try Free](https://img.shields.io/badge/Try%20Free-FalkorDB%20Cloud-FF8101?labelColor=FDE900&style=for-the-badge&link=https://app.falkordb.cloud)](https://app.falkordb.cloud)
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![FalkorDB Docs Readme Banner](https://github.com/user-attachments/assets/201b07e1-ac6d-4593-98cf-e58946d7766c)
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# FalkorDB
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### The Graph platform developers use to achieve accurate GraphRAG for enterprise GenAI
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[![Docker Hub](https://img.shields.io/docker/pulls/falkordb/falkordb?label=Docker)](https://hub.docker.com/r/falkordb/falkordb/)
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[![Discord](https://img.shields.io/discord/1146782921294884966?style=flat-square)](https://discord.gg/ErBEqN9E)
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### About FalkorDB
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FalkorDB delivers an **accurate, multi-tenant RAG solution powered by a low-latency, scalable graph database technology.**
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* Our solution is purpose-built for development teams working with complex, interconnected data—whether structured or unstructured—in real-time or interactive user environments.
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* The system supports the OpenCypher query language with proprietary enhancements that streamline interactions with graph data. Its efficient graph traversal and query capabilities render it well-suited for production environments.
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[![Try Free](https://img.shields.io/badge/Try%20Free-FalkorDB%20Cloud-FF8101?labelColor=FDE900&style=for-the-badge&link=https://app.falkordb.cloud)](https://app.falkordb.cloud)
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### Choose Your Path
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* **Graph Path:** If you're interested in utilizing FalkorDB as a property graph database with OpenCypher support, continue with the sections below.
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* **GraphRAG Path:** If you're aiming to implement advanced graph reasoning and generative AI tasks, jump directly to the [GraphRAG SDK](https://github.com/FalkorDB/GraphRAG-SDK) section [1].
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FalkorDB is a blazing fast graph database used for low latency & high throughput scenarios. Under the hood, it runs [GraphBLAS](http://faculty.cse.tamu.edu/davis/GraphBLAS.html) to perform graph operations using sparse linear algebra.
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## Primary features
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## Primary Features
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* Adopting the [Property Graph Model](https://github.com/opencypher/openCypher/blob/master/docs/property-graph-model.adoc)
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* Adopts the [Property Graph Model](https://github.com/opencypher/openCypher/blob/master/docs/property-graph-model.adoc)
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* Supports [OpenCypher](http://www.opencypher.org/) query language with proprietary extensions
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* Offers [Full-Text Search](/cypher/indexing#full-text-indexing), [Vector Similarly](/cypher/indexing#vector-indexing) & [Numeric indexing](/cypher/indexing).
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* Interacts via either [RESP](https://redis.io/docs/reference/protocol-spec/) and [Bolt](https://en.wikipedia.org/wiki/Bolt_(network_protocol)) protocols
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* Graphs represented as sparse adjacency matrices
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* Supports GraphRAG with the [GraphRAG SDK](https://github.com/FalkorDB/GraphRAG-SDK) for advanced graph reasoning and generative AI tasks.
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## Give it a try
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## Get Started
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Launch an instance using docker, or use [FalkorDB Clouds](https://app.falkordb.cloud)
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