FalkorDB
neo4j
Memgraph
TigerGraph DB
JanusGraph
NetworkX
Amazon Neptune
Azure Cosmos DB
HeidiSQL
DBeaver
DataGrip
MySQL Workbench
phpMyAdmin
Navicat
DbVisualizer
Adminer
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 HeidiSQLFalkorDB's answer
C, Rust, Next.js
FalkorDB's answer
An ultra-low latency Graph Database
FalkorDB's answer
x100 faster than the leading solutions
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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.
There was a need to work with the MS SQL database, but I did not want to install and understand the complex SQL Management Studio program, and this product turned out to be very easy to install and use. For more then 2 month i've used the tool haven't came across any issues.
Based on our record, FalkorDB seems to be more popular. It has been mentiond 3 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 / 3 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 / 3 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 / 3 months ago
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
DBeaver - DBeaver - Universal Database Manager and SQL Client.
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.
DataGrip - Tool for SQL and databases
TigerGraph DB - Application and Data, Data Stores, and Graph Database as a Service
MySQL Workbench - MySQL Workbench is a unified visual tool for database architects, developers, and DBAs.