mage VS mgclient

You can find the MAGE repository on this link.

We will import these 118521 edges, and act as if they are undirected. The Node2Vec algorithm in MAGE accepts parameters whether to treat graph from Memgraph as directed or undirected.

Memgraph introduces the concept of query modules, collections of user-written Cypher procedures intended to extend Cypher by implementing complex graph algorithms. Various query modules are already implemented and ready to use in an open-source project MAGE.

However, there is one more thing that we should really think about when syncing Memgraph and Elasticsearch and that is expandability. The challenge is to build a solution that will need the minimum amount of change when a new method is required. That is why we decided to use Memgraph’s Pythonic capabilities and create a new query module that uses Elasticsearch’s API inside Memgraph’s graph library MAGE.

Memgraph Advanced Graph Extensions, or for short, MAGE, is an open-source graph library that contains implementations of standard and incremental graph algorithms. You can use any of the algorithms as well as implement your own.

MAGE is an open-source repository that contains many Memgraph modules in various programming languages. The overall idea is to extend Memgraph with capabilities that are not part of the core engine. One of the critical design decisions early on was the compatibility with various programming languages to support different application stacks and developers with varying skill sets. Up until now, only C/C++ and Python were first-class citizens of the Memgraph ecosystem, but Rust is quickly running through the front doors!

Memgraph is a graph database in C++ but heavy on Rust as well. The client -> https://github.com/memgraph/rsmgclient (still early, please report any issues). It's possible to write query modules for Memgraph in Rust -> https://github.com/memgraph/mage/tree/main/rust (the "rusty" wrapper).

If you want to do more with your graph data, visit the Memgraph MAGE graph library (and throw us a star ⭐) and take a look at all of the graph algorithms that have been implemented. You can also implement and submit your own algorithms and utility procedures.

Finally, if you are working on your query module and would like to share it with other developers, take a look at the contributing guidelines. We would be more than happy to provide feedback and add the module to the MAGE repository.

We at Memgraph recognize your challenges. In this article, you will learn about the merits of online community detection methods and get acquainted with the LabelRankT algorithm by Xie et al., now available in MAGE 1.1.

For the compiler toolchain, I decided to use Emscripten since it bundles nicely with JS (if you recall from the previous article, the system libraries are exported in JS, which provides a nice native integration). Moreover, Emscripten integrates nicely with cmake, making it easy to extend the current build scripts of mgclient. Therefore, after a set of small changes to the codebase, I managed to add WASM as a compilation target of mgclient. The best part is that the integration is so smooth that you can build it in one go with cmake .. -DWASM=ON && make -j4, and if you are curious about how this all works internally, check out our cmake files GitHub repository.

There is a broad number of drivers in many different programming languages available for both solutions. While Memgraph only maintains a few in-house drivers that it develops and supports (C, C++, Python, Rust), most Neo4j drivers can also be used with Memgraph. This is due to the fact that both solutions use the Bolt protocol, labeled property graph model and Cypher query language.

FROM python:3.8 # Install CMake RUN apt-get update && \ apt-get --yes install cmake # Install mgclient RUN apt-get install -y git cmake make gcc g++ libssl-dev && \ git clone https://github.com/memgraph/mgclient.git /mgclient && \ cd mgclient && \ git checkout dd5dcaaed5d7c8b275fbfd5d2ecbfc5006fa5826 && \ mkdir build && \ cd build && \ cmake .. && \ make && \ make install # Install pymgclient RUN git clone https://github.com/memgraph/pymgclient /pymgclient && \ cd pymgclient && \ python3 setup.py build && \ python3 setup.py install # Install packages COPY requirements.txt ./ RUN pip3 install -r requirements.txt COPY card_fraud.py /app/card_fraud.py WORKDIR /app ENV FLASK_ENV=development ENV LC_ALL=C.UTF-8 ENV LANG=C.UTF-8 ENTRYPOINT ["python3", "card_fraud.py"]