Are you reluctant to switch from a relational database to a graph databases to explore fraud because you believe you first need to be proficient in Cypher to correctly import the data? Be rest assured - there is a Python-friendly approach available within Memgraph!
An in-memory database is a database that is kept in the main memory (RAM) of a computer and controlled by an in-memory database management system. When analyzing information in an in-memory database, only the RAM is used.
A Knowledge Graph is a reusable data layer that is used to answer sophisticated queries across multiple data silos. With contextualized data displayed and organized in the form of tables and graphs, they achieve pinnacle connectivity.
Say hello to GQLAlchemy 1.2, a Python OGM (Object Graph Mapper) that helps you work with graph databases.
Through this guide, you will learn how to use different query builder methods to create, change, get, set, and remove data from Memgraph.
Through this short tutorial, you will learn how to import table data from files stored in local or online storage systems to a Memgraph graph database using GQLAlchemy
Through this guide, you will learn how to start, stop, connect to and monitor Memgraph instances with GQLAlchemy.
Learn how to build applications from bottom to top with the help of GQLAlchemy.
Choose to store python objects partially into an in-memory Graph Database and into an SQLite database on disk.
Learn how to use the GQLAlchemy library to manage data streams and database triggers in Memgraph
A guide to understanding how link prediction works with node2vec algorithm
Through this tutorial, you will learn how to create a basic Flask server, Dockerize an app and connect to Memgraph
Through this tutorial, you will learn how to work with Memgraph from a Python script or a Jupyter Notebook
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
Explore the world of science influencers whose papers are the most cited publications in the world of computer science
Learn how to develop a simple application for visualizing and analyzing the BitClout social network using Memgraph, Python, and use D3.js.
Learn how to productionize your NetworkX algorithms with Memgraph using Cypher procedures and query modules.
Learn the basic principles behind community detection algorithms, their specific implementations, and how you can run them using Python and NetworkX.
In this tutorial, you will learn how to build a simple graph-powered Python fraud detection web application from scratch.