Memgraph
Scalable graph database for real-time analytics, AI workloads, and connected data applications. Compatible with Neo4j and optimized for low-latency queries.
Memgraph is an open-source alternative to:
Memgraph is a high-performance, in-memory graph database designed for real-time analytics and AI workloads. It enables organizations to process and query connected data at scale with millisecond latency, making it ideal for fraud detection, knowledge graphs, logistics optimization, and AI agent memory.
Key Features
- Real-time graph processing: In-memory architecture for sub-millisecond query responses
- Cypher compatibility: Full support for Neo4j's Cypher query language
- Vector search integration: Native support for semantic search and AI workloads
- GraphRAG capabilities: Structured context for AI applications
- High availability & security: Enterprise-grade features including encryption and role-based access control
- ZeroETL: Direct query capabilities without traditional ETL pipelines
- Multi-model support: Handles both property graphs and vector embeddings
- Developer tools: Memgraph Lab (visual interface), Python drivers, and NetworkX compatibility
Tech / Self-Hosting
Memgraph offers both cloud and self-hosted deployment options. The open-source core is available on GitHub, with enterprise features requiring a license. Supports Docker, Kubernetes, and bare-metal installations. Compatible with major cloud providers and offers managed services for production deployments.