Why Memgraph

Unlock a whole new world of capabilities and insights that are near-impossible to achieve using traditional data analysis technologies.

Why Memgraph
Developer Benefits

How Memgraph Improves your Development Process

01
Build and Scale Your Real-Time Graph Apps Faster

Memgraph is built for developer usability and simplicity. It offers broad language support so you can use your favorite programming language, a powerful query language and integrated tools for easy application building - be it a dashboard, data visualization...

02
Graph Analytics on Streaming (and Static) Data

Take full advantage of your streaming data without building time-intensive custom microservices, or worrying about performance engineering and operations. Wrangle your streaming data and build on top of it in an easy and intuitive way without worrying about joins and recursions, solving complex graph data problems in production environments with the fastest and easiest solution.

03
Real-Time Graph Data Visualizations

Make smarter decisions about your graph application development by visualizing and interacting with your graph data in real time. Extracting insights and understanding your results is easier when you can execute ad hoc queries in seconds and immediately observe their impact.

04
Solve Complex Problems

The understanding of complex relationships and interdependencies between different data points is crucial to many decision-making processes, especially in an ever more connected world. Graph analytics have found their way into every major industry, from marketing and financial services to transportation.

Use Cases

Where Can I Use it

Fraud Detection

Advanced graph analytics provides deeper insights, complementing Business Intelligence, and helps organizations prevent potential fraud while protecting customers. Merchants and financial services organizations are estimated to spend $9.3 billion annually on fraud detection and prevention by 2022.

Community Detection

Community detection algorithms are
used to find groups of densely connected components in various networks. The nature of large interconnected networks makes it practically impossible to detect distinct or repetitive patterns manually as well as programatically with less sophisticated methods.

PageRank

The PageRank algorithm measures
the importance of each node within the graph, based on the number incoming relationships and the importance of the corresponding source nodes. The underlying assumption roughly speaking is that a page is only as important as the pages that link to it.

Process Optimization

You’ve got Kafka data from a million sources leading to a complex, fragile, slow “data lake” that you never use? Memgraph gives you everything you need to tame the mess and start using your data immediately.

Route Computation

Accurate and fast path computation is essential for applications such as onboard navigation systems, traffic network routing, delivery systems, etc. To compute these kinds of metrics we can rely on graph algorithms.

Recommendation Engine

A real-time recommendation engine requires the ability to instantly capture any new interests shown in the customer’s current behavior – something that batch processing can’t accomplish but is trivial for graph databases.

Not sure Memgraph is the best fit for your project?

We’re happy to consult and discuss your problem area - and rest assured we’ll keep your best interests at heart. We don’t oversell our solution if there’s no benefit in it for you.

Let's Talk
Free eBook

The Ultimate Introduction To Graph Analytics

Discover what makes graph analytics so powerful and how you can apply them across a variety of use-cases. You will learn about:

  • What is the graph data model and how to build one
  • What are graph algorithms and where to apply them
  • What are some of the most common graph use-cases
The Ultimate Introduction To Graph Analytics eBook graphic