Katana Graph and Intel Collaborate on Graph Analytics Python Library and Metagraph Plug-In

Katana Graph has released a high-performance graph analytics Python library in collaboration with Intel for the benefit of data scientists and the growth of the open core community. The library can also take advantage of the Anaconda Metagraph orchestration layer that provides a common entry point to graph algorithms.

Through full Intel CPU optimization, Katana Graph provides the library for native graph applications such as pathfinding, clustering, and node ranking, among others. Users can collect data in various formats and import them into Katana Graph’s engine to obtain greater insights into their data.

“We are proud to partner with Intel on this initiative within the open source Python community,” said Keshav Pingali, Katana Graph co-founder, and CEO. “At Katana Graph, we are dedicated to empowering data scientists with tools to derive deep value from their data. Through this collaboration with Intel, we are accelerating how end users can write their own algorithms with a Python API.” 

At the heart of Katana Graph’s solution is the Katana Graph Engine with its accompanying partitioner, communication, virtualization, and storage technology modules.

According to Katana Graph, this software, along with the benefit of more than a decade of advanced research in graph technology and high performance computing, will expand the role of graph computing across the technology industry. 

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