Memgraph MAGE

If you need to reap the benefits of both a graph database and Elasticsearch, the new module in Memgraph’s graph library MAGE enables you to easily synchronize those two components using triggers.

The new version of Memgraph’s open-source graph extension library, MAGE, now supports node classification and link prediction algorithms. Install the new version of MAGE if you would like to write custom algorithms faster by using the C++ API, need the igraph algorithms or k-means clustering.

If you believe C++ is simply the best, you’ll be happy to hear that the new Memgraph C++ API enables you to effortlessly build query procedures, functions and other analytics tools using your favourite language. What are you waiting for? Code away!

In recent months, users started to ask more frequently about the ability to run algorithms on a subgraph, and we in Memgraph listen to what our users need. Read more in this post How we designed and implemented graph projection feature

Our journey of creating an optimized shortest paths algorithm that returns all paths of same length. Starting from a MAGE query module and working within Memgraph's core, here is what we learned.

Online algorithms are key for rapid response to changes in streamed graph data

MAGE 1.2 - Full package of dynamic graph algorithms

A step-by-step tutorial on how to identify essential proteins in protein-protein interaction networks using graph analytics

Learn more about the Vehicle Routing Problem on real-world examples and new approaches

A step-by-step tutorial on how to identify essential proteins in protein-protein interaction networks using graph analytics

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