memgraph/memgraph
High-performance open-source in-memory graph database for GraphRAG, AI memory, agentic AI, and real-time graph analytics. Cypher-compatible, built in C++. observed · 2026-08-28
Health v2 · maintenance only
97/100
- Activity 99
- Release rhythm 93
- Longevity 100
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 21
- age_days: 2172
- days_rel: 49
- days_push: 7
- n_releases_24m: 28
Adoption not part of the score
4364 stars · 259 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Memgraph is a high-performance, in-memory graph database written in C++ that is Cypher-compatible and ACID-compliant, with built-in vector, text, and geospatial indexes. It targets GraphRAG pipelines, AI memory systems, agentic AI reasoning, and real-time graph analytics such as fraud detection and network analysis.
Use cases
- run graphrag pipelines with multi-hop traversal and vector search in one query
- store long-term memory for llm agents as a connected graph
- detect fraud in real time by analyzing entity relationships
- migrate from neo4j to a faster in-memory graph database
- run pagerank and community detection on streaming data from kafka
- build a knowledge graph from csv or sql data for ai context
When to choose
- you need sub-millisecond multi-hop graph traversals for AI or analytics workloads
- you want graph traversal and vector similarity search in a single atomic query
- you already use Cypher and want Neo4j compatibility with better performance
- you process streaming data from Kafka, Pulsar, or Redpanda into a live graph
When to avoid
- you need a fully open-source license for commercial use - Memgraph uses BSL/MEL source-available terms
- your dataset exceeds available RAM and you need disk-first storage
- you need a lightweight embedded graph store rather than a server deployment
Facets
service · maturity stable
database vector-database search-engine streaming rag machine-learning analytics databases large-language-models analytics big-data self-hosted cloud cpp python graph-database cypher opencypher in-memory graphrag ai-memory agentic-ai mage neo4j-compatible kafka fraud-detection graph-algorithms bsl-license ai-agents retrieval-augmented-generation linux docker kubernetes
7 sources
- readme: https://github.com/memgraph/memgraph · fetched 2026-08-28 · dc25a51a1a1f
- homepage: https://memgraph.com · fetched 2026-08-29 · 76bfae61a0e3
- site_page: https://memgraph.com/docs · fetched 2026-08-29 · 585aadc04d2b
- site_page: https://memgraph.com/docs/getting-started · fetched 2026-08-29 · 7436b6d9d366
- site_page: https://memgraph.com/about-us · fetched 2026-08-29 · d7d982c4f999
- site_page: https://memgraph.com/tools · fetched 2026-08-29 · 38b45be95ca0
- site_page: https://memgraph.com/pricing · fetched 2026-08-29 · 91f97b80bd46
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| memgraph/memgraph | main | 97 |
For agents
markdown · JSON · MCP: product_card(name="memgraph/memgraph")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem