TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench—a powerful toolkit that enables data scientists to significantly improve ML ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More What do you get when you combine two of the most up-and-coming paradigms ...

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional neural ...

Graph querying of data housed in massive data lakes and data warehouses has been part of the big data and analytics scene for many years, but it hasn’t always been a particularly easy process.

One of the great things about the database market is that there are many different kinds of data and the problems that need to be addressed to store, organize, and query that data are also increasing ...

What Is a Graph Database? Your email has been sent Explore the concept of graph databases, their use cases, benefits, drawbacks, and popular tools. A graph database is a dynamic database management ...

At its Build event in San Francisco, Microsoft just showed off its new add-in frameworks for Office that let developers build applications on top of the company’s productivity apps that will run ...