Software Alternatives, Accelerators & Startups

FalkorDB VS ArangoDB

Compare FalkorDB VS ArangoDB and see what are their differences

FalkorDB logo FalkorDB

Build Fast and Accurate GenAI Apps with GraphRAG at Scale

ArangoDB logo ArangoDB

A distributed open-source database with a flexible data model for documents, graphs, and key-values.
  • FalkorDB
    Image date //
    2025-01-27

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.

  • ArangoDB Landing page
    Landing page //
    2023-01-20

FalkorDB

Pricing URL
-
$ Details
freemium
Release Date
2023 December
Startup details
Country
Israel
Founder(s)
Guy Korland, Roi Lipman, Avi Avni
Employees
10 - 19

FalkorDB features and specs

  • Multi-Tenancy
    10K+ In a single instance
  • Low-Latency
    500x faster than Neo4j

ArangoDB features and specs

  • Graph DB

FalkorDB videos

Auto generating of Knowledge Graph with MindGraph, FalkorDB & OpenAI

More videos:

  • Tutorial - Getting started with FalkorDB SaaS

ArangoDB videos

ArangoDB and Foxx Framework, deeper dive. WHILT#17

Category Popularity

0-100% (relative to FalkorDB and ArangoDB)
Databases
8 8%
92% 92
Graph Databases
13 13%
87% 87
NoSQL Databases
8 8%
92% 92
Developer Tools
100 100%
0% 0

Questions and Answers

As answered by people managing FalkorDB and ArangoDB.

Which are the primary technologies used for building your product?

FalkorDB's answer

C, Rust, Next.js

What makes your product unique?

FalkorDB's answer

An ultra-low latency Graph Database

Why should a person choose your product over its competitors?

FalkorDB's answer

x100 faster than the leading solutions

How would you describe your primary audience?

FalkorDB's answer

Developers, Architects, Data scientists, CTOs

What's the story behind your product?

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.

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare FalkorDB and ArangoDB

FalkorDB Reviews

We have no reviews of FalkorDB yet.
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ArangoDB Reviews

9 Best MongoDB alternatives in 2019
ArangoDB is a native multi-model DBMS system. It supports three data models with one database core and a unified query language AQL. Its query language is declarative which helps you to compare different data access patterns by using a single query.
Source: www.guru99.com
Top 15 Free Graph Databases
ArangoDB is a distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions. ArangoDB
ArangoDB vs Neo4j - What you can't do with Neo4j
Scalability needs and ArangoDB ArangoDB is cluster ready for graphs, documents and key/values. ArangoDB is suitable for e.g. recommendation engines, personalization, Knowledge Graphs or other graph-related use cases. ArangoDB provides special features for scale-up (Vertex-centric indices) and scale-out (SmartGraphs).

Social recommendations and mentions

Based on our record, ArangoDB should be more popular than FalkorDB. It has been mentiond 6 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.

FalkorDB mentions (3)

  • Semantic search alone won't solve relational queries in your LLM retrieval pipeline.
    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
  • Graph database vs relational vs vector vs NoSQL
    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
  • NoLiMA: GPT-4o achieve 99.3% accuracy in short contexts (<1K tokens), performance degrades to 69.7% at 32K tokens.
    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

ArangoDB mentions (6)

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What are some alternatives?

When comparing FalkorDB and ArangoDB, you can also consider the following products

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

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.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

TigerGraph DB - Application and Data, Data Stores, and Graph Database as a Service

Amazon Neptune - Amazon Neptune is a fully managed graph database service that works with highly connected datasets. Learn about the benefits and popular use cases.