About Memgraph
Memgraph is an in-memory graph database that stores data as nodes and the relationships between them. It is built for fast queries over connected data, including GraphRAG for AI and fraud detection.
What it does
Memgraph keeps its graph in memory, which makes reads and writes very fast, and it persists data to disk so it survives restarts. Queries are written in Cypher, a widely used graph query language. The product targets GraphRAG, where an AI system follows relationships between entities instead of relying only on text similarity. It is also used for real-time analytics such as fraud checks, network analysis and data lineage, where the connections between records matter more than the records alone.
Key features
- Graph queries written in Cypher
- In-memory storage for fast reads and writes
- Persistent, ACID compliant data storage
- Multi-hop traversal across relationships
- Graph algorithms to score possible paths
Who it's for
Teams building AI systems that need structured context, fraud and risk teams that look for hidden links between accounts, and engineers who work with network or lineage data.
Pricing and good to know
The product is free to start, and there is a separate enterprise tier for larger needs. The site lists graph sizes from 100 GB to 4 TB, so very large graphs are within scope. Because the graph lives in memory, memory capacity is the main factor to plan for when you size a deployment.
Highlights
- Query connected data with Cypher
- Traverse several relationship hops in one query
- Keep data in memory for low-latency reads
- Store data durably with ACID transactions
- Score and compare alternative paths in a graph
