Memgraph
by Memgraph · In-memory graph database for AI context and real-time analytics
BenchRank score
Screenshots of Memgraph
Homepage
Overview
Memgraph is an in-memory graph database queried with Cypher, used to traverse multi-hop relationships for GraphRAG, AI agent memory and analytics such as fraud detection, data lineage and supply chain modelling. It runs ACID transactions with on-disk persistence, replication, vector search and the MAGE algorithm library, and installs on Linux, macOS or Windows.
- Best for
- Teams building GraphRAG, AI agent memory or real-time graph analytics on an in-memory graph database
- Pricing
- No figures are published: Community Edition is free and open source, Memgraph Cloud offers a free trial, and Enterprise is quoted by memory capacity through sales, with a 30-day trial available.
- Runs on
- Self-hostedCLI
Strengths and trade-offs
Strengths
- Community Edition is free, open source and production-ready
- Cypher plus Neo4j-compatible interfaces and protocols
- Vector search and MAGE algorithm library in the free edition
- Enterprise licence covers queries, compute and replicas with no extra fees
Trade-offs
- No prices published; Enterprise requires a sales conversation
- Cost scales with memory capacity, so large graphs get expensive
- Stated graph sizes run 100 GB–4 TB, bounded by in-memory design
- SSO, RBAC, multi-tenancy and automatic failover are Enterprise-only
How Memgraph markets itself
A structured read of the promise, proof and page design on Memgraph’s captured homepage.
Homepage capture
“The Graph Engine for AI Context”
- Angle: AI-native
- Hero: Abstract graphic
Pricing
Published plans and prices from Memgraph’s own pricing page.
How this score is made up
Each dimension is scored out of 100 and combined into the headline score using fixed weights.
MCP support
Whether an agent can drive the product through the Model Context Protocol, and how much setup that takes.
Documentation
Publicly reachable docs — coverage, freshness, code samples and machine readability.
Agent friendliness
How readable the site is to an automated client: llms.txt, structured data, server-rendered content, crawler access.
Pricing transparency
Whether real prices are published, self-serve signup exists, and usage costs are knowable without a sales call.
Changelog
A public, dated record of what shipped and when — the clearest signal that a product is still alive.
Marketing site structure
Whether the site answers a buyer's questions: clear positioning, the pages that matter, and accessibility.
Page speed
How fast the site loads for real visitors: Chrome UX Report 75th-percentile LCP, INP and CLS, with a Lighthouse mobile run standing in where a site has too little traffic for field data.
Operational trust
Status page and incident history, security disclosure, compliance and data-processing documentation.
Measured, but not part of the score
Useful to know, but not a mark for or against the product — so these do not affect the ranking.
Openness
Source availability, self-hosting, data export and open standards. Scored and shown, but not part of the composite — paid SaaS is not worse for being paid SaaS.
Maintenance
Release cadence and repository activity. Scored and shown, but not part of the composite — it is only measurable for open repositories.
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Where this comes from
The Memgraph pages BenchRank reads when it scores the product — its documentation, release notes, status and security pages, and its repository where there is one.
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