Developers use Memgraph's open-source graph database and its surrounding ecosystem to unlock insights from their data streams.
With Memgraph the possibilities are endless. You can build a powerful recommendation engine for your e-commerce platform or prevent potential fraud. With the PageRank algorithm, you can create your very own social network that measures the importance of each node within the graph based on the number of incoming relationships and the importance of the corresponding source nodes.
Ingest data from any stream to an in-memory graph database equipped with built-in streaming connectors.
Run dynamic as well as traditional graph algorithms by using simple Cypher queries instead of piling SQL joins.
Find patterns and similarities within streaming data that relational data models have no ability to.
In-memory database with built-in streaming connectors. Supports on-disk storage when needed. Memgraph directly connects to your streaming infrastructure and reduces the complexity of your data analysis pipelines.
Visualize graphs, execute ad hoc queries, and optimize performance on data stored in Memgraph. Memgraph Lab is a visual user interface that helps you explore and manipulate the data stored in Memgraph.
An open-source library that contains graph algorithms in the form of query modules you can use right away with Memgraph.
Query graph data with Python by using GQLAlchemy, an object graph mapper and Memgraph client that integrates into your existing Python infrastructure.