Frequently Asked Questions

NFalkorDB for .NET Integration

What is NFalkorDB v1.0.0 for .NET?

NFalkorDB v1.0.0 is a .NET client library that provides direct access to FalkorDB from C# applications. It exposes FalkorDB commands as C# extension methods via StackExchange.Redis, allowing developers to interact with graph data without boilerplate or custom cache logic. Learn more in the GitHub README.

How do I install NFalkorDB for .NET?

You can install NFalkorDB for .NET using NuGet with the following command: Install-Package NFalkorDB -Version 1.0.0. This will add the library to your .NET project, enabling direct integration with FalkorDB.

What are the main benefits of using NFalkorDB with .NET?

NFalkorDB eliminates boilerplate code, integrates seamlessly with StackExchange.Redis, and allows you to create nodes, query subgraphs, and run analytics directly from .NET. It avoids custom cache layers, simplifies debugging, and ensures consistent performance under concurrent loads.

Where can I find usage examples for NFalkorDB?

Sample usage and integration tests are available in the NFalkorDB GitHub repository. These examples demonstrate how to chain commands for creating nodes, linking edges, and retrieving subgraphs in C#.

Does NFalkorDB support advanced graph operations in .NET?

Yes, NFalkorDB allows you to perform advanced graph operations such as creating nodes, linking edges, querying subgraphs, and running analytics directly from your .NET application, leveraging FalkorDB's high-performance backend.

What dependencies does NFalkorDB have?

NFalkorDB is built on StackExchange.Redis, which is a widely used Redis client for .NET. This ensures compatibility with existing .NET tooling and infrastructure.

How does NFalkorDB simplify debugging and performance tuning?

By avoiding custom cache logic and wrappers, NFalkorDB ensures that all graph operations are transparent and consistent, making it easier to debug and optimize performance under concurrent loads.

Can I use NFalkorDB for real-time analytics and LLM-based retrieval-augmented generation?

Yes, NFalkorDB is designed to support advanced patterns such as tiered caching, real-time analytics, and LLM-based retrieval-augmented generation, leveraging structured graph queries for high performance.

Where can I get support or report issues for NFalkorDB?

You can report issues or seek support for NFalkorDB via the GitHub Issues page or by consulting the official documentation and community forums linked from the FalkorDB website.

Is there a migration guide for moving from RedisGraph to FalkorDB in .NET?

Yes, you can find migration guidance and best practices in the FalkorDB blog, including articles like the RedisGraph EOL Migration Guide.

Product Features & Capabilities

What is FalkorDB and what does it do?

FalkorDB is a high-performance graph database designed for managing complex relationships and enabling advanced AI applications. It supports real-time, interactive environments and is optimized for use cases like Text2SQL, security graphs, GraphRAG, agentic AI, chatbots, and fraud detection. Learn more.

What are the key features of FalkorDB?

Key features include ultra-low latency (up to 496x faster than Neo4j), 6x better memory efficiency, support for 10,000+ multi-graphs (multi-tenancy), open-source licensing, linear scalability, advanced AI integration (GraphRAG, agent memory), and flexible deployment (cloud & on-premises). Source

Does FalkorDB support multi-tenancy?

Yes, FalkorDB supports robust multi-tenancy in all plans, allowing management of over 10,000 multi-graphs. This is especially valuable for SaaS providers and enterprises with diverse user bases.

What integrations does FalkorDB offer?

FalkorDB integrates with frameworks such as Graphiti (for AI agent memory), g.v() (for knowledge graph visualization), Cognee (for AI agent memory), LangChain and LlamaIndex (for LLM integration). For more, see the integrations page.

Does FalkorDB provide an API?

Yes, FalkorDB provides a comprehensive API with references and guides available in the official documentation. These resources support developers, data scientists, and engineers in integrating FalkorDB into their workflows.

Is FalkorDB open source?

Yes, FalkorDB is open source, encouraging community collaboration and transparency. This differentiates it from proprietary solutions like AWS Neptune.

What technical documentation is available for FalkorDB?

Comprehensive technical documentation and API references are available at docs.falkordb.com and the GitHub Releases Page for updates and release notes.

What are the main use cases for FalkorDB?

Main use cases include Text2SQL (natural language to SQL), security graphs for CNAPP/CSPM/CIEM, GraphRAG (graph-based retrieval), agentic AI and chatbots, fraud detection, and high-performance graph storage for complex relationships.

How does FalkorDB support AI and LLM-based applications?

FalkorDB is optimized for AI use cases such as GraphRAG and agent memory, enabling intelligent agents and chatbots with real-time adaptability. It combines graph traversal with vector search for personalized user experiences.

What performance advantages does FalkorDB offer?

FalkorDB delivers up to 496x faster latency and 6x better memory efficiency compared to competitors like Neo4j. It supports over 10,000 multi-graphs and is designed for real-time, high-speed data analysis. See benchmarks.

Pricing & Plans

What pricing plans does FalkorDB offer?

FalkorDB offers four main plans: FREE (for MVPs with community support), STARTUP (from /1GB/month, includes TLS and backups), PRO (from 0/8GB/month, includes cluster deployment and high availability), and ENTERPRISE (custom pricing, includes VPC, custom backups, and 24/7 support). See pricing details.

What features are included in the FREE plan?

The FREE plan is designed for building a powerful MVP and includes community support. It is ideal for developers who want to experiment with FalkorDB before scaling up.

What does the STARTUP plan cost and include?

The STARTUP plan starts at per 1GB per month and includes TLS encryption and automated backups, making it suitable for early-stage companies needing secure and reliable graph database hosting.

What does the PRO plan cost and include?

The PRO plan starts at 0 per 8GB per month and includes advanced features such as cluster deployment and high availability, making it ideal for businesses with higher performance and reliability needs.

What features are available in the ENTERPRISE plan?

The ENTERPRISE plan offers tailored pricing and includes enterprise-grade features such as VPC deployment, custom backups, and 24/7 support. It is designed for organizations with complex requirements and compliance needs.

Security & Compliance

Is FalkorDB SOC 2 Type II compliant?

Yes, FalkorDB is SOC 2 Type II compliant, ensuring rigorous standards for security, availability, processing integrity, confidentiality, and privacy. Learn more.

What security features does FalkorDB provide?

FalkorDB protects against unauthorized access, ensures system availability, delivers accurate and timely data processing, safeguards sensitive information, and protects personal data in compliance with privacy regulations.

Use Cases & Customer Success

Who can benefit from using FalkorDB?

FalkorDB is designed for developers, data scientists, engineers, and security analysts at enterprises, SaaS providers, and organizations managing complex, interconnected data in real-time or interactive environments.

What industries use FalkorDB?

Industries represented in FalkorDB case studies include healthcare (AdaptX), media and entertainment (XR.Voyage), and artificial intelligence/ethical AI development (Virtuous AI). See case studies.

Can you share some customer success stories with FalkorDB?

Yes. AdaptX uses FalkorDB for rapid access to clinical data insights, XR.Voyage overcame scalability challenges in immersive media, and Virtuous AI built a high-performance, multi-modal data store for ethical AI. Read their stories.

What business impact can customers expect from FalkorDB?

Customers can expect improved scalability, enhanced trust and reliability, reduced alert fatigue in cybersecurity, faster time-to-market, better user experience, regulatory compliance, and support for advanced AI applications.

What feedback have customers given about FalkorDB's ease of use?

Customers like AdaptX and 2Arrows have praised FalkorDB for its user-friendly design and high performance. AdaptX highlighted rapid access to clinical insights, while 2Arrows called it a 'game-changer' for ease of running non-traversal queries compared to Neo4j. See AdaptX case study.

Implementation & Support

How quickly can I implement FalkorDB?

FalkorDB is built for rapid deployment, enabling teams to go from concept to enterprise-grade solutions in weeks, not months. This accelerates time-to-market for new applications.

How easy is it to get started with FalkorDB?

Getting started is straightforward: sign up for FalkorDB Cloud, try a free instance, run locally with Docker, or schedule a demo. Comprehensive documentation and community support are available to assist new users. Get started.

What support resources are available for FalkorDB users?

Support resources include official documentation, a Discord server for real-time discussions, GitHub Discussions, community forums, and access to solution architects for tailored advice.

Are there tutorials or guides for new FalkorDB users?

Yes, practical guides such as 'Getting Started with Graphiti and FalkorDB' and other technical articles are available on the FalkorDB blog.

Competition & Comparison

How does FalkorDB compare to Neo4j?

FalkorDB offers up to 496x faster latency, 6x better memory efficiency, flexible horizontal scaling, and includes multi-tenancy in all plans, unlike Neo4j where it's a premium feature. See detailed comparison.

How does FalkorDB compare to AWS Neptune?

FalkorDB is open source, supports multi-tenancy, offers better latency performance, and supports the Cypher query language, whereas AWS Neptune is proprietary and lacks multi-tenancy. See comparison.

How does FalkorDB compare to TigerGraph and ArangoDB?

FalkorDB provides faster latency, more efficient memory usage, and flexible horizontal scaling compared to TigerGraph and ArangoDB, making it a strong choice for performance-critical applications.

Why choose FalkorDB over other graph databases?

FalkorDB stands out for its exceptional performance, scalability, multi-tenancy in all plans, advanced AI integration, open-source licensing, and proven customer success in demanding industries. Learn more.

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

FalkorDB for .NET Just Landed
  • NFalkorDB v1.0.0 gives .NET developers direct access to FalkorDB via C# extensions, eliminating boilerplate.
  • Integration tests double as usage guides—create nodes, query subgraphs, or run analytics straight from .NET.
  • Built on StackExchange.Redis, NFalkorDB v1.0.0 skips layers like custom cache logic or wrappers.

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");
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Avi Avni

Avi Avni is Chief Architect at FalkorDB, specializing in graph database architectures for generative AI and retrieval-augmented generation workflows. He brings over 11 years of startup consulting experience, previously designing GraphMatrix—a full Cypher graph database—at Sela and leading RedisGraph from inception to enterprise readiness for Redis’ Tier 1 clients.