Learn how graph databases enhance fraud and anomaly detection by uncovering hidden links across accounts, devices, and behaviors.

From scattered signals to actionable insight, see how graph-powered threat intelligence gives security teams an edge.

Learn how to turn ambiguous data into a high-quality, disambiguated knowledge graph via an agentic approach using Memgraph’s built-in vector search in this hands-on demo.

Memgraph 3.3 and Lab 3.3 are here! Alongside improvements in high availability, one of the standout features in this release is nested indices—a quite unique addition.

Why graph databases are key to powering accurate, real-time RAG systems with LLMs and complex, connected data.

Discover how to convert unstructured Hacker News content into structured, searchable insights using Memgraph’s graph database and Cognee’s AI-powered memory engine.

Learn how to u Memgraph’s AI Toolkit with LangGraph and MCP to build agents that think, act, and query over graphs dynamically.

Discover the Memgraph AI Toolkit, an open-source Cypher-first codebase to build graph-powered AI apps using LLM agents, vector search, and GraphRAG techniques.

Discover how Memgraph and EBCONT turned car images into a queryable knowledge graph using a blend of computer vision, vector search, and GraphRAG in this hands-on Community Call demo.

Cypher generation vs tool invocation: which is better for building reliable graph-based AI assistants? Get the breakdown.

Find out why knowledge graphs are key to personalizing LLMs, improving context, relevance, and real-time insights with GraphRAG.

Discover how to turn unstructured text into a knowledge graph using Memgraph’s vector search in this hands-on demo.

Connect Memgraph to G.V() to run Cypher queries, explore graph data visually, and manage your schema easily in one interactive interface.

Compare fine-tuning vs. RAG to overcome LLM limitations and make enterprise data accessible, dynamic, and useful.

Simplify loading your graph database. Learn about Memgraph's new data migration connectors for DuckDB, Spark, Iceberg, S3, and more enterprise sources.

Multi-tenancy and why it matters, trade-offs, and how Memgraph handles it without breaking your graph.

Discussing the best tools, databases, and frameworks to build a powerful GraphRAG system with real-time, relevant insights.

Missed NASA’s People Graph webinar? Catch the recap and see how graph technology and AI are shaping the future of workforce intelligence.

Explore the key differences between GraphQL and REST APIs and discover why GraphQL is a natural fit for graph databases like Memgraph.

Memgraph has been recognised as a Responsive Company in the Knowledge Graph Market by MarketsandMarkets' 360Quadrants. Learn about this achievement, key industry trends, and how Memgraph 3.0 with GraphRAG technology is enhancing AI context capabilities for enterprise applications.

Learn how to build Agentic RAG with Pagerank using LlamaIndex.

Here’s what our CEO thinks about RAG and how it’s changing

How to build multi-agent system with Memgraph and LlamaIndex.

Learn how to use KNIME with Memgraph to run Cypher queries, build graph models, and analyse connected data using KNIME's low code environment.

We added a support for Memgraph toolkit, to build agentic application with LangGraph and Memgraph.

Stop fine-tuning LLMs. Give them real-time, secure context with Memgraph to deliver accurate, personalized answers.

How to build single-agent system with Memgraph and LlamaIndex.

We're excited to introduce the Memgraph MCP Server, a lightweight server implementation of the Model Context Protocol (MCP) designed to connect Memgraph with LLMs.

Why LLMs like ChatGPT can't query enterprise data and how RAG adds context to make them work for your business.

How LLMs work, their limits with enterprise data, and why tools like RAG and fine-tuning help fill the gaps.

How FI Consulting built a scalable RAG system with Memgraph and DeepSeek—no GPU overkill, no LLM hallucinations.

Query graph data without writing Cypher. GraphChat translates plain English into queries so even non-developers can get answers.

Missed our webinar on Memgraph Lab 3.0? Catch up on the key updates—smarter GraphChat, real-time schema, and team collaboration!

Check out how Hierarchical GraphRAG and Memgraph 3.0 improve knowledge retrieval with Leiden community detection and structured knowledge graphs.

Ditch rigid GraphRAG pipelines—build an AI-powered agent that picks the right tool for every query. Powered by Memgraph 3.0.

Build smarter, faster GenAI apps with Memgraph’s GraphRAG. Use LLMs, graph databases, and dynamic algorithms for real-time insights.

A fast graph database & context engine for GenAI, powering GraphRAG, vector search, and real-time AI-driven insights.

How Volue optimized power grid management with Memgraph’s real-time graph analytics—faster queries, better insights, smarter energy use.

RJ Visser built interactive dashboards with Memgraph to query linked data and integrate Python tools for efficiency.

How to optimize semantic queries, handle high-dimensional embeddings, and query unstructured data efficiently.

Improvements to LangChain and LlamaIndex integrations simplify knowledge graph creation and enhance GraphRAG workflows.

Read how TrustGraph uses chunking, GraphRAG, and Memgraph to tackle unstructured data in complex, regulated industries.

How to extract entities from text with SpaCy, build knowledge graphs in Memgraph, and visualize insights in just a few steps!

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.

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.

How Memgraph's graph database maps and analyzes criminal networks, enabling real-time insights for crime-fighting efforts?

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.

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

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.

Here's how to migrate Neo4j to Memgraph using Compare41.

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

Analyzing and optimizing Bitcoin's Lightning Network using Memgraph in real time.

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.

Integrate vector and graph databases for AI. We cover semantic search, database optimizations, and future trends.

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.

Check out how our AI-driven approach, using ChatGPT, reduced PostgreSQL to Memgraph migration time to just 15 minutes.

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.

How LLMs generate custom CSS-like GSS for dynamic graph visualization in Memgraph, training AI to create GSS.

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.

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.

Discover Memgraph's tools for different schema generation.

Learn how to export your data from Neo4j and painlessly import it to Memgraph while preserving relationships

Guide on querying Memgraph using the Cypher query language

Compare Memgraph's high-performance in-memory graph database with Amazon Neptune's cloud-native scalability and RDF support.

Enable natural language querying in Memgraph Lab with LangChain and LLMs, bridging Cypher expertise and AI-driven queries.

Integrate Confluent's Kafka with Memgraph for efficient data streaming and real-time IoT data analysis using Docker Compose.

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.

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

Compare ArangoDB's multi-model flexibility with Memgraph's in-memory graph performance for real-time analytics and complex queries.

Learn how denormalization boosts query speed and data retrieval in graph databases with large, interconnected datasets.

Explore different open-source database options, their technical features and use cases most suitable for your current need

Exploring how to write complex Cypher queries and mutations in Memgraph to effectively work with graph data

Overview of few interesting visualization tools that can be used in Python and guide on how to implement and use them.

Explore the Berlin subway system using Memgraph Lab, mapping subway stops as nodes and connections as edges in a graph database.

Transition from py2neo to Memgraph's GQLAlchemy for enhanced graph database performance and modern Python support.

Explore why transitioning from Neo4j to Memgraph enhances performance, reduces costs, and provides unmatched technical support.

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

Learn how to use Graphistry with Memgraph and visualize your data set.

Explore Apache License 2.0, a permissive open-source license offering flexibility, freedom, and patent protection for developers.

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.

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

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.

Read on to learn more about a brand new real-time graph visualization of Bluesky, a new social network for microblogging.

Learn about the main differences between Memgraph and NebulaGraph to choose the one that suits your use case best.

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

Explore centrality measures in network analysis, including betweenness centrality, to identify key nodes and optimize networks.

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!

Explore the possibilities of Memgraph and Kubernetes with our latest Helm chart repository.

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.

How to use Graph Notebook with Memgraph in Jupyter notebooks to analyze a supply chain effectively.

Learn how to use JupiterOne’s graph-based security analysis tool Starbase with intuitive graph view backed by Memgraph.

Memgraph and TigerGraph are both powerful graph database solutions. This article compares the features, performance, and pricing models between Memgraph vs. Tigergraph to help you choose the right option for your needs.

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.

This article delves into the world of graph databases, introducing Memgraph as a robust alternative to RedisGraph. As we dive into Memgraph's remarkable features and strengths, we'll uncover why it has emerged as an enticing option for graph-based applications.

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.

Discover the power of graph databases and their role in modern data management. Explore the definition, advantages, and applications of graph databases in this comprehensive article.

Memgraph is preparing new community call and this time with a special guest, Brett Brewer, who will talk about querying Memgraph through an LLM.

In this case study, you will learn how the collaboration between Memgraph and Company X yielded impressive results, including a 135% increase in detection efficiency and savings in the seven-figure range.

PostgreSQL, also known as Postgres, is an open-source relational database management system with a strong reputation for reliability, feature robustness, and performance. It is known for its ability to handle a diverse range of workloads, but what sets it apart from other databases? Uncover the unique advantages of PostgreSQL, explore its core features, and see why it might be the right choice for your next project.

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

Explore the fundamental differences between SQL and NoSQL databases, get to know their features, advantages, and explore examples in this blog.

How databases ensure data consistency using ACID transactions and the impact of isolation levels on your application.

Explore the foundations of graph search algorithms and learn how to leverage them effectively to unlock new possibilities for solving complex problems and advancing your development skills.

This article will guide you through all the factors to consider when choosing a database, providing insights into popular database models to help you make an informed decision.

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.

This is the only deep dive you need to compare different types of NoSQL databases and explore their applications across various industries.

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

How to find credible sources to help you learn more about graphs and apply them to your use case? Save these 7 graph algorithm books and e-resources in the bonus section.

From social networks and biological systems to recommendation engines, graph clustering algorithms enable data scientists to gain insights and make informed decisions that create value.

Graphlytic has introduced support for Memgraph DB and Memgraph Cloud which enables seamless connectivity between your Memgraph instance and any Graphlytic installation.

Choose wisely! The right graph database can make or break your project. Discover how DB-Engines rescues developers from regretful decisions.

Meet the three companies at the Summit and dive into the Integrated Link Analysis for unstructured data powered by AI, NLP and Graph Analytics.

In this article, we will compare two leading graph databases, Memgraph and Neo4j graph database, to help you choose the best platform for your needs.

Improve cybersecurity with Saporo and Memgraph, achieving 10x faster performance and 2x quicker migration for attack surface management.

Discover the differences between relational and graph databases, their respective characteristics, features, and applications. This article also delves into Cypher and SQL query languages, various data modeling techniques, and differences in performance.

A streaming database is a real-time data repository specifically designed to store, accumulate, process and enhance a data stream.

How many recommendation algorithms do you need for a successful recommendation engine? Start with these five and we'll recommend you more!

Learn how to pick the best streaming analytics tool for your use case

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

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.

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?

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.

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.

An in-memory database is a database that is kept in the main memory (RAM) of a computer and controlled by an in-memory database management system. When analyzing information in an in-memory database, only the RAM is used.

Real-time graph analytics combines streaming data technology, graph databases, and graph algorithms to tackle problems not suited for relational databases and batch processing.

What is PageRank algorithm? How can it be used in various graph database use cases? How to use it in Memgraph? If these questions are keeping you up at night, here is a blog post that will finally put your mind at ease.

Get valuable insights into the world of community detection algorithms and their various applications in solving real-world problems in a wide range of use cases. By exploring the underlying structure of networks, patterns and anomalies, community detection algorithms can help you improve the efficiency and effectiveness of your systems and processes

Betweenness centrality is one of many measures you can get from performing a centrality analysis of your data. It identifies important entities in your network that are actually a vulnerability and can bring your processes to a standstill. Dive deeper into this important metric and how it can be used in various use cases.

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!

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.

With the rising number of cyber-attacks followed by the massive digitalization of companies, the right tool is needed to maximize performance and prevent further attacks from happening. We explain why graph databases offer a perfect choice in cybersecurity use cases and why they make your business more secure.

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.

Learn how knowledge graphs and pattern matching in Memgraph can uncover hidden insights, optimize data, and detect fraud.

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.

Little by little, the hosting cost of a graph database can turn out to be quite substantial. Hosting costs are highly correlated with how much resources a database uses, which is not as straightforward as you might think. Find out how expensive it is to host Memgraph and Neo4j instances and why.

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.

Compare Memgraph and Neo4j to find the best open-source graph database for your needs. Discover key features and differences.

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.

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

Building real-time analytical applications require capable infrastructure. Picking the right software infrastructure components can take time and effort. When it comes to graph databases, find out why Memgraph is a fast and powerful real-time graph database.

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.

Use graph databases to unify dispersed data, enhance real-time analysis, and scale efficiently with dynamic algorithms.

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.

With the Introduction to graph analytics with Python course, you will learn all about graphs and how to analyze them. Check out the overview of the graph analytics tools landscape and engaging examples to find out how to use the most powerful network analysis Python tools.

Although networks are an easy concepts to understand, they are poorly managed in many various industries. Learn how graphs can help scale your network topologies and draw conclusions crucial for your business

A lot of companies today have massive amounts of siloed data just sitting there and not being used. No information or knowledge was gained, and no conclusions were made. For the data to be useful, it needs to be interconnected and shaped into a knowledge graph that will produce value for the company. Read how graphs can help!

How Graph Machine Learning and Memgraph can solve fraud detection using Node Classification on real datasets.

The new version of Memgraph’s open-source graph extension library, MAGE, now supports node classification and link prediction algorithms. Install the new version of MAGE if you would like to write custom algorithms faster by using the C++ API, need the igraph algorithms or k-means clustering.

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

Data lineage helps you make informed decisions that reduce costs, streamline operations and power innovation. Discover how stream tech helps with automatically mapping data lineage, and learn how Memgraph integrates with event streaming platforms.

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.

Memgraph delivers results up to 120 times faster than Neo4j while consuming one quarter of the memory!

The data lineage graph is the single source of truth about your organization’s data. Discover how Memgraph can competently handle this use case with its optimized architecture, power data insights and connect to other software.

Find out how to organize data into a graph. Model vehicle insurance claims, incidents, policies and more while preserving the interconnected nature of individual insurance cases.

For every problem in the energy management system, there is a graph algorithm that can point you in the right direction! Here is an overview of the most useful graph algorithms for highlighting weak links, high-risk nodes and many more.

Join a number of graph enthusiasts on the last Graph Data Zagreb meetup in 2022.!

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.

Improve IAM with graph databases for faster data traversal, dynamic vulnerability analysis, and scalable, flexible access management.

The GDPR has placed high demands on organizations doing business in the European Union, mainly focused on how personal data is collected and processed. However, this does not mean it can’t be business as usual again. Find out why graph databases are the best way to achieve GDPR compliance and how they get it done.

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!

Antonio, also known as Fico, joined Memgraph almost three years ago! He started as a student in the Cloud team, but his career path changed as his interest increased. Without further ado, let’s get straight to the point and find out more about Fico’s background, career path, and role in the interview below.

With power being the most powerful asset, it’s still managed by inadequate tools and systems based on tabular data. Good for aggregations and mathematical operations but terrible for actually managing large-scale, highly connected dynamic systems. Luckily, graphs can regain control over energy systems and topologies, and help save millions.

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.

If your data is trapped inside tables and you can’t seem to get satisfying answers to questions that would enhance your business, it’s time to switch to graph databases. Here are three main reasons why!

The world has changed a lot in the past couple of years, and it’s no different for business organizations. More and more businesses no longer have strict hierarchical organizations and people often change teams and projects they work on and resources they need. It is no wonder that if the IAM systems also don’t change, they will no longer be helpful in supporting the organization. Switching to graphs presents a change the IAM systems desperately need.

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.

If a recommendation engine built on relational databases is falling a part due to the bottlenecks made by complex JOINs and never-ending schema changes, there is only one permanent and game changing solution - graph databases.

Complex JOINs necessary for tracking data lineage with relational DBs drag down the speed of analyzing and visualizing the lineage and pinpointing issues and solutions. That is why graph technology is perfect to model and manage data lineage! Not convinced? Read the post to find out more.

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.

Sometimes choosing graphs solutions isn’t the only step you can take to mitigate risks. In case fraudsters foolishly think they can outsmart an analytics team, they probably haven’t come across their new best friend - fraud detection systems enhanced with machine learning models.

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.

Have you ever wondered who writes all the technical documentation here at Memgraph or who’s answering questions and helping developers through Discord and Stack Overflow? Read more to find out.

DRS is a web application that helps to navigate through documentation by giving you page recommendations based on your input URL.

Did you ever fall down some bottomless pit of bad data modeling? Our inter Adrian sure did, but he learned a lot from it - how to recognize the pitfalls and how to avoid them in the future! Hope his experience helps you… but let’s be honest, we never really learn from other people’s mistakes, so if you fall be sure to yell for help!

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

We want to introduce you to Sasa, a frontend engineer on the Platform team responsible for developing and designing Memgraph Lab. In this blog post, Sasa talks about his onboarding experience and how he got his socks knocked off during the technical interview.

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

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.

Discover what six summer interns learned and achieved during their time with us in Memgraph.

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.

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!

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

The summer break is over and we’re back in action - it’s time for our 6th Graph Data Zagreb Meetup! This time we are having two talks: Track Data Lineage With a Graph Database + Memgraph Internship Projects.

Four days of summer, sea, company alignment, and fun pretty much sums up our second company retreat. We brought all of our employees together and spent a few amazing days both in Zagreb and on the island of Mali Losinj.

How to build docker images for multiple architectures

We kicked off this year’s summer internship with a meetup at our Zagreb office. Six amazing students from PMF and FER are eager to start this summer and gain real-work experience.

A deep dive into Drug Discovery with Biomedical Knowledge Graphs by AstraZeneca ends the Spring season of Graph Data Zagreb.

Industry leaders in the drug discovery and development area use graph technology. Here’s why

On the occasion of Memgraph 6th birthday, Founders Dominik and Marko made a video about their Memgraph journey while visiting San Francisco.

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.

Movie ratings from MovieLens are incoming, but you are still not sure what to watch over the weekend? Create your own movie recommendation system.

Analyze the Art Blocks transaction data, projects and communities in real-time with Memgraph

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

Recommending books is hard. Thanks to the Amazon books dataset and insights from graph analytics, you can build your own. Here’s how.

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.

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

In-memory databases primarily rely on RAM storage instead of using hard or external disks for memory storage. Let’s take a look at how in-memory databases work along with some use cases in data science.

Learn what is Docker Compose and how it can help you in the application development process.

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.

Memgraph is organizing its fourth Graph Data Zagreb Meetup. The topic of our next meetup is “How to Transform Bitcoin Blockchain Into a Graph!”

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.

Last week, at WESPA Spaces, on May 4, 2022, Memgraph held its the third edition of Graph Data Zagreb meetup for over 60 participants. Katarina Šupe, developer relations engineer created an excellent presentation for graph enthusiasts and Game of Thrones fans.

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

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.

Meet Kostas - a passionate C++ engineer from Greece who joined the Core team more than a year ago

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.

Online algorithms are key for rapid response to changes in streamed graph data

MAGE 1.2 - Full package of dynamic graph algorithms

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

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

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

Through this guide, you will learn how to use different query builder methods to create, change, get, set, and remove data from Memgraph.

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

Through this guide, you will learn how to start, stop, connect to and monitor Memgraph instances with 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.

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.

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.

Analyzing the European energy crisis and dependency on Russian natural gas imports

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

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

Choose the best streaming database for real-time analytics: Amazon Kinesis, Memgraph, Apache Storm, Apache Kafka, or StreamSQL.

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.

how Memgraph engineers sharpened their coding skills and bonded during the Advent of Code 2021 challenge.

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

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

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.

Learn how to use the GQLAlchemy library to manage data streams and database triggers in Memgraph

Learn more about the benefits of real-time analytics and how they allow you to get key insights almost instantaneously.

From health insurance to home office budget - take a look at some of the benefits we offer to our employees

Learn how to receive real-time data with WebSocket from Flask server using React on the client side and draw updates with D3.js

We attended the annual Mutimir conference organized by Penkala to learn about exciting research opportunities and meet Croatia's young scientists.

Explore graph-related articles on algorithms, streaming data, and applications—perfect for holiday reading and learning.

Remote, Work from home, or Hybrid - what does it all mean in Memgraph?

MAGE 1.1 - Applying Graph Magic to Stream processing

Explore rumor spreading in a contact network as it changes through time with online community detection

Explore a network of retweets using a dynamic PageRank algorithm and a graph database

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

Learn how to connect to a Pulsar cluster, create an Art Blocks NFT database in Memgraph and analyze streaming sales

A basic overview of the architecture and features offered by Apache Pulsar and Apache Kafka

Through this tutorial, you will learn how to connect to a Redpanda stream from Memgraph and analyze the graph data

A short story about working with librdkafka

Memgraph 2.1 is here! Welcome, Pulsar and Redpanda!

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

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

Through this tutorial, you will learn how to create a basic Flask server, Dockerize an app and connect to Memgraph

Learn how to create a real-time recommendation engine with the Online Node2Vec embedding algorithm

I sat down with Jure Bajic, our Core Software Engineer to gain a deeper understanding of the process of changing teams, what he values at work and in Memgraph. author: Martina Dominkovic

Through this tutorial, you will learn how to work with Memgraph from a Python script or a Jupyter Notebook

Learn how to get Twitch data, find the most interesting statistics from the Twitch network and visualize the output of different MAGE algorithms on ingested data in real-time

The whole company went together on a 4-day retreat, and this is what it looked like

Join the Challenge and create graph solutions for awesome rewards!

Join the Challenge and create graph solutions for awsome rewards!

Learn how to get Twitch data, find the most interesting statistics from the Twitch network and visualize the output of different MAGE algorithms on ingested data in real-time

Learn how to scrape Twitch data, find the most interesting statistics from the Twitch network and visualize the output of different graph algorithms

Check out what it takes to develop a recommendation engine with graph analytics

Join the annual Hacktoberfest and contribute to open source projects

Find out how Memgraph works under the hood

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

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.

How we overcame the hurdles of working remotely

Network analysis is rapidly gaining popularity throughout different industries. Find out why!

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

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

The engineering team behind Memgraph spent a week developing some pretty cool apps with the power of graph analytics.

Take a look at how Memgraph organized a fully remote summer internship for its newest graph aficionados.

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!

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

An overview of the newly added Rust query modules support

Explore the world of science influencers whose papers are the most cited publications in the world of computer science

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"

Memgraph is back and trigger-happy!

Memgraph is participating in the Microsoft Build 2021 conference!

Analyzing Eurovision Song Contest results from 1975 to 2019 with graph analytics

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

Memgraph is participating in the RockPaperStartups 2021 conference!

Learn how to develop a simple application for visualizing and analyzing the BitClout social network using Memgraph, Python, and use D3.js.

In this tutorial, you will learn about the code assignment problem in telecommunication networks and how to solve it in a simple yet effective way using graph algorithms and Memgraph.

Learn about the benefits of using a graph database instead of SQL in terms of data modeling, querying, and development speed and flexibility.

Learn how to productionize your NetworkX algorithms with Memgraph using Cypher procedures and query modules.

Learn how to model, visualize, and navigate a complex transportation network using graph algorithms, Cypher, Memgraph, and Memgraph Lab

Learn the basic principles behind community detection algorithms, their specific implementations, and how you can run them using Python and NetworkX.

Learn how to build a flight network analysis graph-based ASP.NET application using Memgraph, C#, and D3.js.

Learn how to extend the Cypher query language by implementing a few simple custom procedures to load and export data in a JSON format using Memgraph MAGE and Python.

In this tutorial, you will learn how to build a simple graph-powered Python fraud detection web application from scratch.

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!

By using the LRP algorithm, we delivered J-Packs to everyone in the company for Xmas!

Discover how to visualize graph data on a world map in Memgraph Lab

Discover how to customize your graph visualisations using the new scripting lanugage.

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.

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

Learn how graph databases can offer powerful data modeling and analysis capabilities your business can leverage to easily model real-world complex systems and answer challenging questions.

Learn how to leverage breadth-first search and dijkstra's algorithm to build a route planning application with Memgraph and Cypher.

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

A step-by-step tutorial for installing Memgraph Platform on macOS

The Memgraph community forum is the best place to get fast and accurate answers from both our team and other Memgraph developers.

A step-by-step tutorial for installing Memgraph and Memgraph Lab on Windows 10

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.

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.

Learn about the differences between static and dynamic data, real-time data sources and ways of analyzing streaming data

Memgraph and FactGem Partner to Give Clients Access to Real-Time, Transaction Based Analytics.