# memgraph
**Repository Path**: joo2019/memgraph
## Basic Information
- **Project Name**: memgraph
- **Description**: No description available
- **Primary Language**: C++
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-04-23
- **Last Updated**: 2026-04-23
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
---
## :clipboard: Description
Memgraph is a high-performance, in-memory graph database that powers real-time
AI context and graph analytics. Built in C/C++, it serves as the graph engine
for GraphRAG pipelines, AI memory systems, and agentic workflows — delivering
sub-millisecond multi-hop traversals for any system that needs structured,
connected context alongside semantic vector or text search.
Memgraph provides both in a single query layer: built-in text and vector
indexes for similarity search combined with full graph traversal, so retrieval
pipelines can run as a single atomic database operation instead of being
scattered across multiple systems.
The same architecture drives real-time graph analytics for fraud detection,
network analysis, infrastructure monitoring, and other operational workloads
where performance matters. Memgraph is fully compatible with Neo4j’s Cypher
query language, ACID-compliant, and highly available.
## :zap: Features
#### AI & Graph Intelligence
- **Indexes** - Built-in vector indexes power hybrid graph retrieval with
similarity search in a single query, alongside text and geospatial indexes for
keyword and location-aware queries.
- **[MAGE](mage/README.md) algorithm library** - 40+ graph algorithms in C++,
Python, and CUDA including PageRank, community detection, GNN-based link
prediction, temporal graph networks, embeddings, and native ML.
- **Atomic GraphRAG** - Pivot search, graph expansion, ranking, and prompt
assembly expressed as a single Cypher query.
- **LLM utility module** - Graph-aware context formatting for large language
models.
- **[AI Toolkit](https://github.com/memgraph/ai-toolkit)** - Integrations with
popular agentic frameworks, MCP server, and ready-made components for building
GraphRAG, AI memory, and agent workflows on top of Memgraph.
- **Real-time schema introspection** - `SHOW SCHEMA INFO` returns the full
graph ontology for Text2Cypher and AI agent integration.
#### Performance & Query Power
- **In-memory C/C++ engine** - Sub-millisecond traversals with [benchmarked
performance](https://memgraph.com/benchgraph).
- **Deep-path traversals** - Accumulators and path filtering without additional
application logic.
- **Custom query modules** - Extend with Python, Rust, and C/C++ code natively.
- **Parallel query execution** - Concurrent query processing for
high-throughput workloads.
- **Native Parquet & JSONL loading** - Load data directly from Parquet and
JSONL files on local disk, S3, or HTTP endpoints.
- **Streaming support** - Ingest from Kafka, Pulsar, and RedPanda with dynamic
graph algorithms that react to changes in real time.
#### Enterprise
- **High availability** - Raft-based coordination with automatic failover.
- **Multi-tenancy** - Isolated databases with per-tenant role assignments.
- **Fine-grained access control** - Role-based and label-based permissions at
the node and edge level.
- **Authentication & authorization** - SSO integration, user impersonation, and
30+ granular permissions.
- **Encryption in transit, monitoring, backup & restore.**
## :video_game: Memgraph Playground
You don't need to install anything to try out Memgraph. Check out our
**[Memgraph Playground](https://playground.memgraph.com/)** sandboxes in your
browser.
## :floppy_disk: Download & Install
### Windows
[](https://memgraph.com/docs/memgraph/install-memgraph-on-windows-docker)
[](https://memgraph.com/docs/memgraph/install-memgraph-on-windows-wsl)
### macOS
[](https://memgraph.com/docs/memgraph/install-memgraph-on-macos-docker)
[](https://memgraph.com/docs/memgraph/install-memgraph-on-ubuntu)
### Linux
[](https://memgraph.com/docs/memgraph/install-memgraph-on-linux-docker)
[](https://memgraph.com/docs/memgraph/install-memgraph-on-debian)
[](https://memgraph.com/docs/memgraph/install-memgraph-on-ubuntu)
[](https://memgraph.com/docs/memgraph/install-memgraph-from-rpm)
[](https://memgraph.com/docs/memgraph/install-memgraph-from-rpm)
[](https://memgraph.com/docs/memgraph/install-memgraph-from-rpm)
### Kubernetes
[](https://github.com/memgraph/helm-charts)
Deploy Memgraph on Kubernetes using the official [Helm charts](https://github.com/memgraph/helm-charts),
including charts for standalone and high-availability deployments:
```bash
helm repo add memgraph https://memgraph.github.io/helm-charts
helm install my-memgraph memgraph/memgraph
```
You can find the binaries and Docker images on the [Download
Hub](https://memgraph.com/download) and the installation instructions in the
[official documentation](https://memgraph.com/docs/memgraph/installation).
## :rocket: Daily Builds
Stay on the cutting edge with the latest features and improvements by using
[Memgraph Daily Builds](https://memgraph.github.io/daily-builds/). Daily builds
are updated frequently and allow you to test new capabilities before they reach
stable releases.
## :cloud: Memgraph Cloud
Check out [Memgraph Cloud](https://memgraph.com/docs/memgraph-cloud) - a cloud
service fully managed on AWS and available in 6 geographic regions around the
world. Memgraph Cloud allows you to create projects with Enterprise instances
of MemgraphDB from your browser.
## :link: Connect to Memgraph
[Connect to the
database](https://memgraph.com/docs/memgraph/connect-to-memgraph) using
Memgraph Lab, mgconsole, various drivers (Python, C/C++ and others) and
WebSocket.
### :microscope: Memgraph Lab
Visualize graphs and play with queries to understand your data. [Memgraph
Lab](https://memgraph.com/docs/memgraph-lab) is a user interface that helps you
explore and manipulate the data stored in Memgraph. Visualize graphs, execute
ad hoc queries, and optimize their performance.
## :file_folder: Import data
[Import data](https://memgraph.com/docs/memgraph/import-data) into Memgraph
using Kafka, RedPanda or Pulsar streams, CSV, JSON, Parquet, and JSONL files
(from local disk, S3, or HTTP), or Cypher commands.
## :bulb: Best Practices
The [memgraph/best-practices](https://github.com/memgraph/best-practices)
repository contains ready-to-use examples covering graph modeling, data import,
query optimization, GraphRAG, high-availability deployment, and more.
## :world_map: Roadmap
See what's coming next on the
[memgraph/roadmap](https://github.com/memgraph/roadmap).
## :bookmark_tabs: Documentation
The Memgraph documentation is available at
[memgraph.com/docs](https://memgraph.com/docs).
## :question: Configuration
Command line options that Memgraph accepts are available in the [reference
guide](https://memgraph.com/docs/memgraph/reference-guide/configuration).
## :trophy: Contributing
Welcome to the heart of Memgraph development! We're on a mission to supercharge
Memgraph, making it faster, more user-friendly, and even more powerful. We owe
a big thanks to our fantastic community of contributors who help us fix bugs
and bring incredible improvements to life. If you're passionate about databases
and open source, here's your chance to make a difference!
### Compile from Source
Learn how to download, compile and run Memgraph from source with the [Quick
Start](https://memgraph.notion.site/Quick-Start-82a99a85e62a4e3d89f6a9fb6d35626d)
guide.
### Explore Memgraph Internals
Interested in the nuts and bolts of Memgraph? Our [internals
documentation](https://memgraph.notion.site/Memgraph-Internals-12b69132d67a417898972927d6870bd2)
is where you can uncover the inner workings of Memgraph's architecture, learn
how to build the project from scratch, and discover the secrets of effective
contributions. Dive deep into the database!
### Dive into the Contributing Guide
Ready to jump into the action? Explore our [contributing
guide](CONTRIBUTING.md) to get the inside scoop on how we develop Memgraph.
It's your roadmap for suggesting bug fixes and enhancements. Contribute your
skills and ideas!
### Code of Conduct
Our commitment to a respectful and professional community is unwavering. Every
participant in Memgraph is expected to adhere to a stringent Code of Conduct.
Please carefully review [the complete text](CODE_OF_CONDUCT.md) to gain a
comprehensive understanding of the behaviors that are both expected and
explicitly prohibited.
We maintain a zero-tolerance policy towards any violations. Our shared
commitment to this Code of Conduct ensures that Memgraph remains a place where
integrity and excellence are paramount.
### :scroll: License
Memgraph Community is available under the [BSL
license](./licenses/BSL.txt). Memgraph Enterprise is available under the
[MEL license](./licenses/MEL.pdf).
## :star: Special Thanks
We're grateful to all contributors, especially external ones, who have helped
improve Memgraph through bug fixes, features, and documentation. Thank you for
making Memgraph better!
## :busts_in_silhouette: Community
- :purple_heart: [**Discord**](https://discord.gg/memgraph)
- :ocean: [**Stack Overflow**](https://stackoverflow.com/questions/tagged/memgraphdb)
- :bird: [**Twitter**](https://twitter.com/memgraphdb)
- :movie_camera:
[**YouTube**](https://www.youtube.com/channel/UCZ3HOJvHGxtQ_JHxOselBYg)
