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++.
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What is Memgraph?
Memgraph is an open-source, in-memory graph database built for real-time streaming and dynamic analytics environments. It is powered by a C/C++ query engine that delivers sub-millisecond traversals and handles 1,000+ transactions per second for both reads and writes. Memgraph is compatible with Neo4j's Cypher query language and Bolt protocol, making migration straightforward for existing graph database users.
Key features include built-in streaming connectors for Kafka, Redpanda, and Pulsar; four pre-optimized graph algorithms (BFS, DFS, Weighted Shortest Path, All Shortest Paths); the MAGE graph algorithm library with NVIDIA cuGraph GPU-powered algorithms; Memgraph Lab for visual graph exploration; ACID compliance with persistence via write-ahead logging and periodic snapshots; high availability with automatic failover and replication; and support for GraphRAG, AI memory, and agentic AI workloads.
Memgraph is ideal for developers, data scientists, and teams building fraud detection systems, network analysis tools, knowledge graphs, identity & access management systems, supply chain networks, and AI applications requiring real-time graph reasoning. It serves enterprises like NASA, Cedars-Sinai, and Capitec Bank who need to process millions of daily cases or manage complex interconnected data.
Memgraph pricing
Pricing model: Freemium
Memgraph offers a fully functional Community Edition that is open-source and free forever, including Memgraph DB, Memgraph Lab, mgconsole CLI, and MAGE graph algorithm library. Memgraph Cloud is a fully-managed service with a 14-day free trial, deployed across 6 AWS regions with instance sizes from 2GB to 32GB RAM. Pricing for Cloud can be estimated using the Cost Calculator or viewed at Project rates. Memgraph Enterprise offers a free 30-day trial and includes advanced features like multi-tenancy, SSO with Entra ID and Okta. Enterprise is available through the AWS Marketplace.
Memgraph pros
- Open-source and free Community Edition forever
- In-memory architecture delivers sub-millisecond traversals
- 1,000+ transactions per second for reads and writes
- Neo4j-compatible with Cypher query language and Bolt protocol
- Built-in streaming connectors for Kafka, Redpanda, Pulsar
- ACID-compliant with persistence via WAL and snapshots
- Four pre-optimized graph algorithms out of the box
- MAGE library with 100+ graph algorithms including NVIDIA cuGraph GPU support
- Memgraph Lab visual interface for querying and visualization
- High availability with automatic failover and replication
- Vertical scaling up to 1B nodes and 10B edges
- Supports GraphRAG, AI memory, and agentic AI workloads
- Multi-tenancy support in Enterprise edition
- SSO integration with Entra ID and Okta
- Python client libraries with LangChain and LlamaIndex integrations
- Prometheus-compatible monitoring metrics
- Encryption in transit with industry-standard libraries
- Role-based access control with LDAP/PAM integration
Memgraph cons
- No horizontal scaling for write queries (no sharding support)
- Graph size limited by available RAM
- Requires twice as much RAM as data size for optimal performance
- Data not automatically indexed during import (manual indexing required)
- Replication can bottleneck highly parallel workflows
- SYNC replication slows commit times
- No GCP availability for Memgraph Cloud
- Maximum 3 projects and 5 snapshots for new Cloud users
- IP address may change when pausing/resuming Cloud projects
- No password reset available for forgotten Cloud project passwords
Frequently asked questions about Memgraph
What is Memgraph?
Memgraph is an open-source in-memory graph database built for teams that expect highly performant, advanced analytical insights. It is compatible with Neo4j (but up to 8x faster) and powered by a C/C++ query engine to handle real-time use cases at enterprise scale. Memgraph supports strongly consistent ACID transactions and uses the standardized Cypher query language over Bolt protocol.
What are the benefits of being an in-memory graph database?
Storing data in RAM eliminates the need to physically read from disk, which involves slow physical processes like seeking and waiting. In-memory databases access and add data almost instantly, making them ideal for applications requiring fast data processing, real-time analytics, and quick response times.
What use cases is Memgraph best suited for?
Memgraph is best suited for use cases with complex data relationships that require real-time processing and high scalability. Examples include fraud detection, network analysis, data lineage, knowledge graphs, identity & access management, and supply chain modeling.
How does Memgraph compare to other graph databases regarding performance?
Memgraph typically outperforms many other graph databases in speed and scalability. Key factors are its in-memory architecture and a query engine written in C++. It offers label and label-property indexes and a custom visualization library. Benchmarks show it is up to 8x faster than Neo4j.
Is Memgraph a distributed database?
Memgraph supports horizontal scaling of read queries using replication. It does not support horizontal scaling of write queries via sharding because sharded clusters become complex, error-prone systems requiring advanced management and more DevOps resources. Single-machine systems are easier to manage with lower maintenance costs.
How does Memgraph ensure persistency and durability?
Memgraph uses two mechanisms: write-ahead logging (WAL) and periodic snapshot creation. Each database modification is recorded in a log file before being written to the database. Memgraph periodically takes snapshots during runtime. On startup, the database recovers from the most recent snapshot file, and if needed, reconstructs state using the WAL file.
How much RAM do I need for my graph?
We recommend twice as many GB of RAM as the data size. If you have 8 GB of data, have at least 16 GB of RAM. Actual memory needs depend on query complexity and concurrent users. The more graph objects a query returns, the more RAM is required.
What is MAGE?
Memgraph Advanced Graph Extensions (MAGE) is an open-source repository containing graph algorithms and utility modules. It corresponds to APOC in Neo4j but is free and open source. The library includes dynamic algorithms for real-time data, NetworkX and igraph integrations, Elasticsearch synchronization, and NVIDIA GPU-powered algorithms.
What is Memgraph Lab?
Memgraph Lab is a lightweight visual user interface that enables you to write and execute Cypher queries and algorithms, visualize graph data using the Orb library, import and export data, generate data schema, view and optimize query performance, develop custom procedures in Python, and manage stream connections.
Can I try out Memgraph Enterprise before making a decision?
Yes, Memgraph offers a free 30-day Memgraph Enterprise Trial. You can send a request via the form on their website to start the trial.