Useful resources for learning and working with Memgraph
Memgraph is an open source graph database built for real time streaming data, compatible with Neo4j. It is an in-memory graph database that uses Cypher as a query language.
- Memgraph Lab - a visual user interface that helps you explore and manipulate the data stored in Memgraph.
- GQLAlchemy - a standalone Object Grap Mapper (OGM) for Python that allows you to write object-oriented code to communicate with graph databases.
- MAGE - an open-source library that contains graph algorithms in the form of query modules you can use right away with our graph database.
- Graph Database vs Relational Database
- How to migrate from Neo4j to Memgraph
- Temporal graph neural networks with PyTorch - How to create a simple recommendation engine on an Amazon dataset.
- How to use GQLAlchemy query builder?
- How to manage Memgraph Docker instances in Python
- Importing Table Data into a Graph Database with GQLAlchemy
- Exploring a Twitter Network with Memgraph in a Jupyter Notebook
- Memgraph 2.1 - Live Demo with Dominik, CEO & Marko, CTO.
- Graph-based stream processing with Apache Kafka
- MAGE 1.1 Live Demo - Analyzing a Twitter network with PageRank, node2vec & Community detection.
- GQLAlchemy 1.1 - Demo.
- First steps with Memgraph
- Graph modeling
- Implement a custom query module in Python
- Install MemgraphDB and Memgraph Lab on Windows 10
- Style your graphs in Memgraph Lab
- Migrate from RDBMS to Memgraph
- Graph stream processing with Kafka
- Social network analysis with NetworkX
- Understanding music (with query modules
- Analyzing Interactions in a Slack Communication Network
- How to build a Spotify Recommendation Engine using Kafka and Memgraph
- Visualizing and Analyzing Reddit In Real-Time with Kafka and Memgraph
- Building a BitClout Social Network Visualization App With Memgraph and D3.js
- How to Build a Flight Network Analysis Graph-Based ASP.NET Application with Memgraph, C#, and D3.js
- How to Develop a Credit Card Fraud Detection Application using Memgraph, Flask, and D3.js
- Exploring Interpersonal Relationships in the Bible
- How to Implement Custom JSON Utility Procedures With Memgraph MAGE and Python
- How to Write Custom Cypher Procedures with NetworkX and Memgraph
- Influencers among computer scientists
- Modeling, Visualizing, and Navigating a Transportation Network with Memgraph
- Optimizing Telco Networks With Graph Coloring & Memgraph MAGE
- Running Community Detection with Memgraph and Python NetworkX
- Python - driver for connecting to Memgraph using Python.
- Rust - driver for connecting to Memgraph using Rust.
- C# - driver for connecting to Memgraph using C#.
- Java - driver for connecting to Memgraph using Java.
- Go - driver for connecting to Memgraph using Go.
- Node.js - driver for connecting to Memgraph using Node.js.
- JavaScript - driver for connecting to Memgraph using JavaScript.
- PHP - driver for connecting to Memgraph using PHP.
- Analyze Infrastructure Networks with Dynamic Betweenness Centrality
- Monitoring a Dynamic Contact Network with Online Community Detection
- LabelRankT - Community Detection in Dynamic Environment.
- Link prediction with Node2Vec in Physics Collaboration Network
- How Node2Vec works - A random walk-based node embedding method.
- Introduction to Node Embedding
- Recommendation System Using Online Node2Vec with Memgraph MAGE
- Twitch Streaming Graph Analysis
- Identifying Essential Proteins using Betweenness Centrality & Memgraph MAGE
- Optimizing Telco Networks With Graph Coloring & Memgraph MAGE
- Vislet - Visualize geographic data in Memgraph Lab.
- How to style your graphs in Memgraph Lab
- Air Traffic Routing with Memgraph
- Building a Recommendation System using Memgraph
- How to Visualize a Social Network in Python with a Graph Database: Flask + Docker + D3.js
Contributions welcome! Read the contribution guidelines first.