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
Memgraph is coming to Amsterdam! Our DevRel team, Katarina and Ivan are visiting Amsterdam to present at some exciting meetup groups.
Meet Benjamin - our only Netherlands' based software engineer who joined the Core team exactly one year ago
Through this short tutorial, you will learn how to install Memgraph, connect to it from a Jupyter Notebook and perform data analysis using graph algorithms.
Memgraph is organizing its second Graph Data Zagreb meetup, where you can discuss the latest topics in areas such as graph databases, graph processing, graph analytics, and graph theory.
Learn how to migrate a dataset from Neo4j to Memgraph using CSV files.
This article will explore 20 of the most common graph algorithms and various ways to use them in real-life scenarios.
Read about our first Graph Data Zagreb meetup and what topics were covered.
Find out more about the onboarding process in Memgraph.
Real-time process optimization and supply chain scheduling are just some of the use cases for graph technology in the chemical industry. Read more about graph use cases in the production of industrial chemicals and how Memgraph helps.
In today’s era of highly developed information systems, one of the key tasks is to seek out the shortest path in the network – from the beginning point to the endpoint.
When applying for developer roles, the interviewer might ask you to solve coding problems during technical interviews. This article will help you understand some of the most fundamental ones like BFS, DFS and Dijkstra's algorithm.
Analyzing the European energy crisis and dependency on Russian natural gas imports
Memgraph 2.2 is here! Welcome, Apple M1 and WebSocket!
This article outlines the main differences between the graph databases Neo4j and Memgraph.
If you are interested in how performance management cycles improve Memgraph''s overall success, this blog post is for you.
Learn the Cypher query language through our simple and informative 10 day email course
Some use cases in data analysis require near-instantaneous processing of data. To make it happen, you need tools for real-time data analysis that support the use of continuous queries.
The fastest to run any graph algorithm on your data is by using Memgraph and MAGE. It’s super easy. Download Memgraph, import your data, pick one of the most popular graph algorithms, and start crunching the numbers.
Did you ever wonder how databases are built and what’s going on in the background of everything you see? We asked Memgraph’s Core team to give us a glimpse into their everyday processes and experiences.
It’s been a month since it finished, but it is never a bad time to share what our engineers were up to and how they kept their coding skills sharp during the Advent period. Dive in to find out more!
A streaming database is a real-time data repository specifically designed to store, accumulate, process and enhance a data stream.
Real-time graph analytics combines streaming data technology, graph databases, and graph algorithms to tackle problems not suited for relational databases and batch processing.
Memgraph is organizing the Graph Data Zagreb meetup, where you can discuss the latest topics in areas such as graph databases, graph processing, graph analytics, and graph theory.
Stream processing is a type of big data architecture in which the data is analyzed in real-time
In this article, you can learn the difference between stream processing vs batch processing, and get to know the basic use cases for each.
Say hello to GQLAlchemy 1.1, a Python OGM (Object Graph Mapper) that helps you work with graph databases.
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.