Read how Memgraph integrates vector search with graph databases for fast, semantic, and similarity-based queries.

Indexes and uniqueness constraints in Memgraph, a guide to skip list implementation.

How Cedars-Sinai uses Memgraph to enhance AutoML for Alzheimer's research, driving predictive accuracy and drug discovery.

Precina Health using GraphRAG to help patients manage Type 2 diabetes at scale, using a mix of real-time data, AI, and personalized care.

Key differences that developers need to be aware of when migrating between these two graph databases.

Using graph-based techniques with Memgraph to enhance static analyzers for precise vulnerability detection.

Optimize Cypher queries with Memgraph. Learn about query plans, caching, and configurations for better performance.

Check out how Memgraph outperforms Neo4j in write speeds with detailed benchmarks and insights on database performance.

Enhance security and streamline user management with Memgraph's new SSO feature.

Read about the most efficient methods for large-scale, high-speed graph data import with minimal resources.

Learn how LLMs and graph databases boost community engagement in our webinar with insights from Orbit's Steeve Bete.

Get a behind-the-scenes look at how Orbit developed a secure and efficient GraphQL API on Memgraph.

A short guide into the things to consider and optimize when dealing with large graph dataset.

Guide on querying Memgraph using the Cypher query language

Introduction to data structures, offering examples of each structure and illustrating how they could be represented in Memgraph

Running Memgraph with the Go Fiber web-framework is a powerful combination for building high-performance web applications. Here is a the step-by-step recipe for integrating Memgraph with Go Fiber.

Persisting data is one of the important features of every database. Stay with us to learn more about the durability theory and how Memgraph turns theory into practice!

In this blog post, our very own intern, Patrik, shares his experience creating a backing for a powerful knowledge extraction engine.

In this article, Oleksandr, one of Memgraph’s amazing interns, shares insights on open-source contribution and the story behind Memgraph and LangChain.

How database snapshots optimize data management by capturing real-time changes efficiently and conserving storage.

Learn about Oleksandr's perspective on creating a GitHub LLM analytics tool as part of Memgraph's intern program this summer.

Explore how ODIN integrates Memgraph with Obsidian to transform note-taking into a dynamic knowledge graph for efficient data management.

Understand the importance of query execution plans in optimizing your queries for better performance. Learn how to analyze and optimize your paths effectively.

Enhance the speed of query execution with our detailed guide. Optimize your database performance and boost productivity.

Both disk and in-memory databases have their pros and cons and can be used in a variety of applications. This blog offers insights into how larger-than-memory architecture can be used to get the best of both worlds!

Dive into the world of key-value databases in this comprehensive guide. Uncover the unique characteristics, real-world applications, benefits, and limitations of key-value databases. Ideal for developers, tech founders, and researchers alike.

If you’re unsure when to use a NoSQL database, read this blog post and learn its advantages and disadvantages. Whether you’re a developer, data engineer, or decision maker, this blog post will provide insights into modern databases and how they can boost your projects and organizations.

Learn all about cosine similarity and how to calculate it using mathematical formulas or your favorite programming language. With the help of diverse Python libraries, you'll smoothly enter the world of machine learning, natural language processing, and information retrieval.

This blog post explains the nuisances of parallel processing and database recovery, how modern computer architectures can be utilized to better serve the needs of the user in the case of recovery, and how Memgraph specifically deals with this issue.

Unravel the terms and conditions of the MIT License, from permission notices to liability clauses, and understand its role in the distribution and modification of MIT licensed code. With the MIT License, developers and organizations alike can navigate the complexities of software distribution while shaping a healthy, collaborative, and inclusive community around their projects.

Explore how you can use Prometheus, a time-series database that enables countless applications, to seamlessly monitor and react to performance changes in Memgraph.

Learn how to generate a data model for the popular TV show Money Heist, import the data, and query the database using ChatGPT.

Optimize your Memgraph configuration with Benchgraph for actionable performance insights and enhanced efficiency.

Read on to learn about how open-source licenses emerged and which license to choose for your project.

An open-source license is a legal agreement that allows users to access, use, modify, and distribute software or source code freely. This article explores the different types of licenses and their implications for developers.

Why Benchgraph? Developing and maintaining a product is a never-ending phase. And proper performance testing is necessary to maintain database performance characteristics during its whole lifecycle. To ensure the consistency of Memgraph’s performance, we’re introducing Memgraph's in-house benchmarking tool.

LOAD CSV is a Cypher clause used for importing data from CSV file format. The clause reads row by row from a CSV file, binds the contents of the parsed row to the variable you specified, and populates the database if it is empty or appends new data to an existing dataset.

One of the fundamental ways of securing online accounts and digital assets is using strong passwords. However, even the strongest passwords can be compromised if they are not properly encrypted and stored. So, how does password encryption work?

Developing a solution that will make the database select an optimal index is a challenging task, since there is incomplete information available. That is why it always boils down to a bunch of estimations. Find out what estimations Memgraph’s query engine uses as default, and how to make the engine to be even more precise.

Hacker News is a website that contains content from the tech industry and to find yourself among its most popular posters sometimes seems a miracle! To break the mystery around it, I tried to knowledge-hack it with Kafka and PageRank algorithm - read on to find out what I discovered!

The Conference on Innovative Data Systems Research (CIDR) is a systems-oriented conference organized every two years since 2003. Check out what interesting people, talks and papers made Memgraph’s CTO Marko excited about the future of graphs.

Find out how you can minimize decision-making risks when dealing with networks by using Memgraph as the one-and-only tool for a complete analysis.

Read about our seventh Graph Data Zagreb meetup and what topics were covered.

Explore GNNs, build a link prediction module, and create a recommendation system using Memgraph's MAGE library.

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!

If you are spending more time writing code to develop, deploy and manage your graph projects, it’s time you tried Memgraph. It will allow you to focus on the data analysis and free you from all that time-consuming coding.

Optimize your data infrastructure with Memgraph's dynamic graph analytics, ensuring reliable, scalable data lineage management.

Are your NetworkX algorithms taking even more and more time to produce the results you need to finish up your research? Or the application reached a critical point and its starting to lag due to increase in data analysis? Could Memgraph tackle the same computations in less time? I think you probably know the answer is “Doh!” but here are the numbers to prove it.

When NetworkX can no longer handle the analysis and vizualisation requirements of your project, and you are tired of constantly reloading data, find out how you can utilize Memgraph to get your graph data analysis back on track.

Accelerate graph analytics with Memgraph's MAGE library, featuring a new C++ API for high-performance custom queries and modules.

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.

Security is playing a big role in the era of big data. To comply with the modern standards of privacy and compliance, we upgraded our security system to be able to authorize the graph on the node and relationship level. Find out how we did it here!

Sometimes in life, you have to roll up your sleeves and do the dirty work yourself. It's exhausting but pays off big time. That's exactly how it felt to build a visualization engine from scratch and then watch with what speed and elegance it renders complex graph structures. So if you are thinking about building a visualization engine, stop right there... we already did it! Pay attention!

Are you tired of bland-looking graphs with limited relationship and node styles? Do you need some color and pictures in your graph life? So did we, until we created Graph Style Script! Now our graphs are bursting with life, and so can yours! What is GSS and how to use it, read this blog post to find out!

Orb is an open-source library developed by Memgraph you can use to visualize graphs by adding just a few lines to your frontend code. This blog post will show you all the cool features Orb offers and how to implement them in your project. Or don't and have slow and appalling graph visualizations - it's your choice. Seriously, use it... it's very easy and fun!

You can't always get what you want, but if you try sometimes, well, you might find, you get what you need. We took The Rolling Stones' advice and tried really hard to find the visualization tool that we need... It didn't really turn out as we wanted, or needed, but at least we had fun testing some software.

The world of version control is getting more interesting each day. Learn what Git, GitHub, and GitHubCLI have in common and master version control!

How to build docker images for multiple architectures

Always wanted to identify the most influential developer within your GitHub network? Check out how by using PageRank.

We have a special guest, Michaël Ughetto, a graph data scientist from AstraZeneca. Michaël will discuss how AstraZeneca ingests data sources in the Biological Insights Knowledge Graph (BIKG) and distribute it to data scientists and domain experts.

Top Python libraries for building and optimizing Knowledge Graphs, including Pykg2vec, PyKEEN, AmpliGraph connectivity.

Query languages used for graph data management are called graph query languages (GQLs). Below are the popular graphDB query languages that provide a way to unpack information in graphs. Let’s dive into the details of popular query languages with their pros and cons.

Using profilers can be tricky, but by understanding and combining them you can pinpoint the bottleneck in your application. In this article you can read about how we combined Callgrind and gperftools to investigate the significant slowdown after rewriting our Bolt server.

The second part of the series deep dives into the WebAssembly ecosystem. Compilers, build systems and more!

The last part of the series introduces the very first Memgraph WASM client jsmgclient.

In the first part of the series, Kostas explores the idea of introducing WASM based clients for Memgraph.

Build a graph recommendation engine using Temporal Graph Neural Networks (TGNs) for label classification and link prediction.

Memgraph is organizing its third Graph Data Zagreb meetup. Join us to discuss the latest topics in the world of graphs.

Read about our second Graph Data Zagreb meetup and what topics were covered.

Meet Benjamin - our only Netherlands' based software engineer who joined the Core team exactly one year ago

This article will explore 20 of the most common graph algorithms and various ways to use them in real-life scenarios.

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

Learn the Cypher query language through our simple and informative 10 day email course

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.

Stream processing is a type of big data architecture in which the data is analyzed in real-time

Learn the key differences between batch and stream processing, their use cases, and when to use each approach.

An in-depth guide to understanding the dynamic node2vec algorithm and its advantages over static algorithms on streaming data

Discover how to detect communities in dynamic networks quickly with LabelRankT

A guide to understanding how link prediction works with node2vec algorithm

Learn the theory behind how to deal with streaming graph data by using Dynamic PageRank

Learn about a graph-based embedding technique for mapping nodes into a low-dimensional space

Find out what node embeddings are, how to generate them and where they can be used

A short story about working with librdkafka

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

Join the Challenge and create graph solutions for awesome rewards!

Join the Challenge and create graph solutions for awsome rewards!

Find out how Memgraph works under the hood

We’re launching Memgraph to bring the power of Graph Applications to every developer

We created a Slack Bot that measures a user's influence and activity in a Slack workspace

Learn how to ingest Reddit data, visualize it as a graph and perform sentiment analysis.

Learn how to write well structured and easily understandable Cypher queries

Learn how to visualize family trees and work with live data using Memgraph and Cypher

A simple error often turns into a full-fledged developer journey when you're trying to find the best solution

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

Learn the Cypher query language through our simple and informative 10 day email course

Use the GQLAlchemy library for easier and more intuitive interactions with Memgraph in Python"

Learn how to implement custom Cypher procedures using query modules and the NetworkX Python library.

Learn about how we implemented replication capabilities in Memgraph. In this post, we discuss our approach, challenges, and solutions.

How to build a Python web application for visualizing a Social Network Graph in Python with Docker, Flask and D3.js

This new release makes it possible to install the pymgclient 1.0.0 on Windows, and macOS. It also makes the installation on Linux much easier, and delivers improved stability.