Learn about built-in algorithms like DFS, BFS, WSP, and ASP, and discover how to optimize graph queries for large-scale environments. Perfect for developers and data scientists seeking robust graph management solutions.

Explore the Memgraph Graph Analytics engine's in-memory analytical mode for efficient graph data management. Learn how it optimizes rapid data imports and enhances performance in our detailed blog post.

Check out when and why to use Memgraph’s in-memory and on-disk storage modes with our detailed guide to database performance and ACID compliance.

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

Discover how LLMs & graph databases can improve community engagement in our latest webinar with insights from Orbit's Steeve Bete.

Check out how University of West Florida researchers used Memgraph to boost ML for cyber threat detection in their latest study.

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

Discover Memgraph's tools for different schema generation.

Getting a quote is easy. But doesn’t paint a full picture. Here are the reasons why jumping on a quick call makes much more sense.

Developer success is crucial in Memgraph and with the help of community channels our developers can enjoy their journey.

Learn about advanced features of Memgraph Enterprise, tailored for larger organizations and more complex use cases.

Discover the exciting synergy of LangChain and Memgraph: An extraordinary integration that introduces an unmatched natural language interface to seamlessly interact with your Memgraph database.

To offer the fairest comparison to other databases, we’ve developed and launched Benchgraph, where you can easily run benchmarks on your own workloads. In this article, Memgraph answers some of the community’s common questions about benchmarking.

Exciting news! Memgraph, the super-fast open-source graph database for streaming and a Neo4j alternative, is partnering with Linkurious, the expert in graph visualization and analytics solutions.

How do you know if your Memgraph configuration is achieving optimal performance? From now on, Benchgraph will be at your disposal to get performance insights!

Memgraph 2.7 now supports another storage mode, which enables you to work on data inside a database without ACID compliance. Once you understand how multiversion concurrency control works in Memgraph, you will also figure out why it can prevent you from importing data faster.

If you need to reap the benefits of both a graph database and Elasticsearch, the new module in Memgraph’s graph library MAGE enables you to easily synchronize those two components using triggers.

As a vast number of use cases in cybersecurity involves network-like representation of data, we outline why Memgraph is the best graph database for you in terms of performance, analytics and visualizations.

People tend to update versions of their code project dependencies without inspecting security impacts on their code. In this article, we use Memgraph to analyze Python package vulnerabilities when updating dependencies and provide you with a performant solution using known and reported vulnerabilities.

Optimizing a supply chain network can get really messy if you can’t identify dependant products, correctly schedule processes and find critical points in the pipeline. With Memgraph, you can accelerate your supply chain pipeline and build a complete analysis tool to increase the shipments of your goods.

Making decisions that point your business in the right direction is much easier with knowledge graphs. But, to create a knowledge graph, you need to gather all the data scattered in different silos, analyze the current connections between data points and discover new connections. It’s a complex task, but graph databases, such as Memgraph, make it a manageable one.

As networks consist of highly connected data, with Memgraph’s in-memory storage you can analyze network topologies quickly to gain insights from static or real-time data. Discover critical points in the network or component dependencies, optimize resources and run what-if scenarios, then present those findings visually to extract every last bit of information.

Start next year with a whole new range of features and graph algorithms to gain insights that will make it a happy year indeed! Developed features include improved security, benchmark tests, projected graph visualization, better code suggestion support, C++ API, node classification and link prediction, to name just a few.

Check out how Memgraph handles the visualization of complex graph structures found in insurance data that will allow you to comprehend and synthesize large amounts of new information more efficiently.

It’s true every recommendation engine requires a performant database to analyze the data and provide the recommendation, but why exactly does Memgraph stand out? Easy - C++, in-memory, real-time analytics! Three things to change the recommendation game.

Find vulnerabilities and security issues, or perform any other data analysis in your Identity and Access Management system with Memgraph, and ensure you are running a smooth operation.

If you require an energy management system that is scalable, fault-tolerant, and performant, Memgraph is the go-to solution! Analyze highly connected power grids or gas pipelines to make meaningful decisions and improve the impact on your business, the people and the environment around you.

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!

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.

There are a couple of steps to follow to move off of your antiquated IAM system and make it more effective. Here is a to-do list to make it a smooth transition.

If you believe C++ is simply the best, you’ll be happy to hear that the new Memgraph C++ API enables you to effortlessly build query procedures, functions and other analytics tools using your favourite language. What are you waiting for? Code away!

Summer has been a busy time for us. This rainy but extensive release of Memgraph brings you four significant features that are bound to make your life easier. As always, there are also bug fixes and smaller but nice improvements to avoid painful debugging moments as much as possible.

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

Another Graph Data Zagreb is behind us. This time we had two conversations. In the first part, Manta gave us presentation about Data Lineage, and in the second part students who had their summer internships at Memgraph showcased the projects they worked on.

If you’re familiar with Memgraph or just started exploring its products, you must have heard about MAGE. But how did it all start, who came up with the idea, and who are the masterminds behind the product? Read more in this post!

We are super excited to share a real honest review of Memgraph with you! The review was created by Ashleigh Faith, a data scientist and researcher, and she hosted our DevRel Engineers, Katarina Šupe and Ivan Despot.

Dive into the new, in browser capabilities that Memgraph Lab and Cloud unlock when analyzing your data streams in the graph domain.

Load custom functions, Bolt over WebSocket implementation and FOREACH clause introduction will allow even easier development.

MAGE 1.2 - Full package of dynamic graph algorithms

We’ve rolled out Benchgraph, our in-house tool to benchmark Memgraph (or Neo4j) on your custom workload. And here is how you can do that!

Say hello to GQLAlchemy 1.2, a Python OGM (Object Graph Mapper) that helps you work with graph databases.

Memgraph 2.2 is here! Welcome, Apple M1 and WebSocket!

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.

Say hello to GQLAlchemy 1.1, a Python OGM (Object Graph Mapper) that helps you work with graph databases.

MAGE 1.1 - Applying Graph Magic to Stream processing

Memgraph 2.1 is here! Welcome, Pulsar and Redpanda!

Find out how Memgraph works under the hood

Memgraph 2.0 is here! We are finally source available and ready to tame your streams.

Memgraph now includes a few more cool features such as Kafka connections and new isolation levels

We are proud to announce the public launch of Memgraph Cloud 2.0. With a brand new UI, exciting new features, and simple pricing, building real-time graph applications has never been easier!

An overview of the newly added Rust query modules support

Memgraph is back and trigger-happy!

Analyze the BitClout network to find out which content creators have the most supporters and are worth investing in

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.

Memgraph 1.3 is here and it brings you high availability replication!

Memgraph 1.2 is here! One of the biggest changes in this release is the addition of Bolt v4 and v4.1 support. In this post, we will explore what exactly is the Bolt protocol, what it brings to the table, and how we implemented it into Memgraph.

Learn how by introducing a new storage engine, encoding and compressing properties on both nodes and edges, and leveraging skip lists as an indexing data structure, we were able to reduce memory usage by as much as 50% and improve throughput towards near-linear scalability.

Take a look at common airplane routing procedures and learn how to use Memgraph Lab to calculate and show results related to them

Learn how to build a recommendation engine with Memgraph using an objective approach.

We are proud to announce the general availability of Memgraph 1.0! Memgraph is an in-memory, native, transactional graph database engineered to support real-time applications.

We're happy to announce that Memgraph drivers for Python and C languages, as well as Memgraph CLI command line interface are now published.

Over the course of ten weeks, we had four interns join Memgraph. They worked directly on the Memgraph product.