Learn how to develop a simple application for visualizing and analyzing the BitClout social network using Memgraph, Python, and use D3.js.
Introduction
BitClout is a new decentralized social network that lets you speculate on (the worth of) people and posts with real money. It’s built from the ground up as its own custom blockchain. Its architecture is similar to Bitcoin’s, except that it supports complex social network models like posts, profiles, follows, speculation features, and much more at a significantly higher throughput and scale. Like Bitcoin, BitClout is a fully open-source project and there is no company behind it, it’s just coins and code.
In this tutorial, you’ll learn how to develop a simple application for visualizing and analyzing the BitClout social…
In this tutorial, you will learn how to build a simple graph-powered Python fraud detection web application from scratch.
Introduction
There is a large and ever-growing number of use cases for graph databases and many of them are centered around one important functionality: relationship traversals. While in traditional relational databases the concept of foreign keys seems like a simple and efficient idea, the truth is that they result in very complex joins and self-joins when the dataset becomes too inter-related.
Graph databases offer powerful data modeling and analysis capabilities for many real-world problems such as social networks, business relationships, dependencies, shipping…
Learn about the benefits of using a graph database instead of SQL in terms of data modeling, querying, and development speed and flexibility.
Introduction
Graph databases provide a much faster and more intuitive way to model and query your data compared to traditional relational databases. In a previous article, we discussed the main differences between a graph database and a relational database, what kind of use-cases are best suited for each database type, and what are their strengths and weaknesses.
Choosing the right tool for the right job is critical to speed up development, ensure flexibility, and avoid operational complexity as…
Learn how to extend the Cypher query language by implementing a few simple custom procedures to load and export data in JSON format using Memgraph MAGE and Python.
Introduction
Oftentimes you find yourself unable to come up with the perfect query that fits the problem at hand. Every query language has its disadvantages and Cypher is no exception. But thankfully, there is always the option of writing your own custom procedures.
Memgraph introduces the concept of query modules which are collections of custom Cypher procedures. You can implement them using a Python or C API.
In this tutorial, you will go through the process of implementing a few simple utility procedures to load and export data in a JSON format.
Introducing Memgraph MAGE
MAGE stands for Memgraph Advanced Graph Extensions. It’s an…
Hands-on Tutorials
Introduction
When you think about a web application, a graph database doesn’t usually spring to mind. Instead, most people just take the familiar route of using an SQL database to store information. While this is perfectly acceptable for most use cases there are sometimes those that would see tremendous benefits by using a graph database. In this tutorial, I will show you how to make a basic web application using Flask that stores all of its information in a graph database. …
Ivan Despot
Developer Relations Engineer and Computer science graduate. I am also a nerd about network science, web development, and product management.
