FalkorDB for .NET Just Landed — NFalkorDB v1.0.0 Now Live

FalkorDB for .NET Just Landed

NFalkorDB directly calls the FalkorDB Graph Database  with minimal overhead, standardized API patterns, and integration with existing .NET tooling so you don’t have to wrestle with custom code.

Installation is straightforward:

				
					Install-Package NFalkorDB -Version 1.0.0.

				
			

In practice, you can use enough sample usage from the integration tests in the NFalkorDB repository, which demonstrate how to chain RedisGraph commands for typical operations like creating nodes, linking edges, and retrieving subgraphs.

This is done without incurring separate caching layers or re-implementing logic in a hidden corner of your codebase, and that approach not only simplifies debugging but also ensures consistent performance under concurrent loads, letting you center your engineering efforts on advanced patterns like tiered caching, real-time analytics, or LLM-based retrieval-augmented generation that pivot seamlessly on structured graph queries.

NFalkorDB exposes FalkorDB commands as C# extension methods through StackExchange.Redis. flowchart

Get Started

NFalkorDB exposes FalkorDB commands as C# extension methods through StackExchange.Redis.

Code example:

				
					// Connect the database and pick a Graph
  ConnectionMultiplexer muxr = ConnectionMultiplexer.Connect(ConnectionString).
  Graph graph = new FalkorDB(muxr.GetDatabase()).SelectGraph("social");

  // Create the Graph
  graph.Query("""CREATE (:Rider {name:'Valentino Rossi'})-[:rides]->(:Team {name:'Yamaha'}),
           (:Rider {name:'Dani Pedrosa'})-[:rides]->(:Team {name:'Honda'}),
           (:Rider {name:'Andrea Dovizioso'})-[:rides]->(:Team {name:'Ducati'})""");

  // Query the Graph
  ResultSet resultSet = graph.ReadOnlyQuery("MATCH (a:person)-[r:knows]->(b:person) RETURN a, r, b");

				
			

Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.

USE CASES

SOLUTIONS

Simply ontology creation, knowledge graph creation, and agent orchestrator

Explainer

Explainer

Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.

COMPARE

Avi Tel-Or

CTO at Intel Ignite Tel-Aviv

I enjoy using FalkorDB in the GraphRAG solution I'm working on.

As a developer, using graphs also gives me better visibility into what the algorithm does, when it fails, and how it could be improved. Doing that with similarity scoring is much less intuitive.

Dec 2, 2024

Ultra-fast, multi-tenant graph database using sparse matrix representations and linear algebra, ideal for highly technical teams that handle complex data in real-time, resulting in fewer hallucinations and more accurate responses from LLMs.

RESOURCES

COMMUNITY