Unlock a whole new world of capabilities and insights that are near-impossible to achieve using traditional data analysis technologies.
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...
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
Discover what makes graph analytics so powerful and how you can apply them across a variety of use-cases. You will learn about: