memgraph

Memgraph is an in‑memory graph database written in C++ and Cypher‑compatible. The platform is aimed at AI and real‑time analytics workloads, GraphRAG, AI memory, agentic AI, fraud detection, and network analysis, by delivering sub‑millisecond traversals and supporting graph sizes from 100 GB to 4 TB. The Community Edition is free forever and includes a Python client, LangChain and LlamaIndex integrations, and an installation script that works on Linux, macOS, and Windows.

The engine stores data as a fully connected graph. You can import documents in PDF, XLSX, CSV, and SQL formats; the database builds nodes and relationships automatically, creating a knowledge graph that you can query in real time. Real‑time graph reasoning is enabled by combining vector search with multi‑hop traversal. For example, a GraphRAG workflow first retrieves a text chunk by similarity, then traverses the graph to follow relationships between entities, providing context that purely text‑based retrieval cannot reach. The same mechanism works for AI memory: long‑term memory is organized into semantic, episodic, and procedural nodes, and an LLM can request any of these types via a Cypher query and receive a structured result in milliseconds.

Agentic AI use cases rely on the graph as a path‑finding engine. A user query triggers a traversal that explores possible action sequences; edge scores represent the likelihood of each step, and the graph itself traces the decision path. The auditability of the path is exposed through the graph's structure, so the reasoning can be inspected or compared with alternative paths. These features make Memgraph suitable for teams that need transparent, auditable decision logic, such as security operations or compliance departments. It is not designed for simple flat‑table lookups or for scenarios that do not involve relationships between entities.

Performance figures are provided in the documentation: sub‑millisecond traversals, 1,000+ transactions per second for reads and writes, and ACID compliance when persistence is enabled. The system can be started with a single command and is compatible with Neo4j's Cypher syntax, making migration easier. However, the site does not publish pricing for enterprise editions, nor does it provide explicit benchmarks for specific workloads beyond the stated numbers. The documentation also lacks detailed code examples for complex multi‑step queries, so developers may need to refer to the official docs for deeper guidance.

Key features