FalkorDB
neo4j
Memgraph
TigerGraph DB
Amazon Neptune
ArangoDB
Ontotext Graph DB
JanusGraph
Apache Cassandra
Redis
MongoDB
ArangoDB
PostgreSQL
neo4j
OrientDB
MySQL
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 Apache CassandraFalkorDB's answer
C, Rust, Next.js
FalkorDB's answer
An ultra-low latency Graph Database
FalkorDB's answer
x100 faster than the leading solutions
FalkorDB's answer
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.
Based on our record, Apache Cassandra seems to be a lot more popular than FalkorDB. While we know about 44 links to Apache Cassandra, we've tracked only 3 mentions of FalkorDB. 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 / about 2 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 / about 2 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
In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / 12 days ago
All messages are persisted durably for two minutes, but Pub/Sub channels can be configured to persist messages for longer periods of time using the persisted messages feature. Persisted messages are additionally written to Cassandra. Multiple copies of the message are stored in a quorum of globally-distributed Cassandra nodes. - Source: dev.to / 6 months ago
Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers without a single point of failure. - Source: dev.to / 10 months ago
Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / 12 months ago
On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra. - Source: dev.to / about 1 year ago
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
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.