Check out how to use Memgraph vector search to find similar movies by analyzing plot embeddings with a step-by-step guide.

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

Learn how Memgraph and LlamaIndex build smarter GenAI apps by turning unstructured data into dynamic, queryable knowledge graphs.

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

Check out how GraphChat lets you talk to your graph database with LLMs, simplifying queries and insights.

Find out more about Lab for graph data visualization, Cypher queries, and real-time insights for experts and beginners alike.

Discover how graph databases improve supply chain management and how HIWE IT uses Memgraph for powerful analytics apps.

Learn how Memgraph’s full snapshots and Write-Ahead Logging (WAL) ensure data durability and efficient recovery.

Compare high availability and replication features in Memgraph Community and Enterprise editions for database resilience.

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

Explore Memgraph's data typed and learn how to use them effectively in your graph database.

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.

Optimizing building automation with digital twins using Memgraph for real-time monitoring and efficient management.

Explore Memgraph's enterprise-ready features: multi-tenancy, high availability, monitoring, and Kubernetes integration.

Learn more about the flexibility of Memgraph Cypher implementation with advanced path traversals and custom query modules.

Deep dive into how Memgraph's security features work to protect your data and ensure compliance.

Memgraph is enterprise-ready with multi-tenancy, high availability, security, and advanced monitoring features.

Integrate LLMs with Memgraph using LangChain for RAG systems and build GenAI applications easily.

How Sayari uses Memgraph for real-time analysis on a billion-node graph for risk analysis.

Optimize Memgraph queries. Explore profiling, indexing, and query parameterization for peak graph database performance.

Ensure uptime and performance with Memgraph’s High Availability Automatic Failover, offering resilience and real-time support.

See how Paysure Solutions uses Memgraph for real-time payment authorization, tackling technical challenges and optimizations.

Memgraph's new multi-tenancy feature enables isolated, secure, and cost-effective graph database management on a single server.

Check out how Microchip uses Memgraph's graphs to enhance LLM chatbot accuracy and response quality in real-world use.

Learn about DFS, BFS, WSP, ASP algorithms, and optimize graph queries for large-scale environments.

Memgraph's in-memory analytical mode for efficient graph data management, optimizing rapid data imports and performance.

Find out when and why to use Memgraph’s in-memory and on-disk storage mode. Our guide to performance and ACID compliance.

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.

Discover how University of West Florida researchers used Memgraph to enhance ML accuracy for detecting cyber threats.

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.

Memgraph and benchmarking. We focuse on performance impacts of read/write operations, tail latency, and caching.

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.

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

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.

Optimize cybersecurity with Memgraph, high-performance graph database for efficient threat analysis and scalable data management.

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.

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

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

Simplify benchmarking with Benchgraph for custom workloads, performance insights, and comparisons on Memgraph or Neo4j.

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.

How Memgraph Lab enhances air traffic control by optimizing flight paths, emergency landings, and storm evasion with graph databases.

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

Memgraph 1.0 is now production-ready, offering high-performance, in-memory graph database with Cypher support.

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.