Kinetica, the engine for the Extreme Data Economy, today announced it is making open source code available to integrate with RAPIDS open source software, a new machine learning training stack introduced by NVIDIA. The combination of RAPIDS and Kinetica allows data scientists and data engineers to reimagine artificial intelligence by exploring, training, visualizing, and integrating machine intelligence into smart analytical applications while leveraging the accelerated computing power of the GPU.
As AI becomes central to enterprise strategies, it is essential to streamline data science and data engineering processes. RAPIDS leverages the power of NVIDIA GPUs to reduce AI model training time from days to minutes. Kinetica combines a GPU database, real-time analytical techniques (location intelligence, time series, text search), and the ability to run analytics and pre-trained machine learning models in-database. Together, RAPIDS and Kinetica provide enterprises with a concrete way to realize the end-to-end impact of AI, whether it be driving cars, stocking warehouses, or making personalized recommendations.
“We’re excited to support Apache Arrow, a core component of accelerated analytics on the GPU. Our latest open source capabilities enable us to seamlessly integrate with RAPIDS across the GPU-powered data ecosystem,” said Nima Negahban, co-founder and CTO of Kinetica. “While NVIDIA drives model development and training, Kinetica drives operationalization and deployment of those models in-database, so enterprises gain maximum insight from their data.”
“Companies are increasingly data-driven, but speed is of the essence to use this data,” said Jeffrey Tseng, head of product for AI Infrastructure at NVIDIA. “With RAPIDS and Kinetica, enterprises can leverage the power of the GPU and advanced analytics across the model development toolchain and dramatically simplify and speed up the data science pipeline.”
The Kinetica integration is based on the Apache Arrow project, enabling Kinetica and RAPIDS to run seamlessly on the GPU and communicate without copying data to the CPU. Kinetica is making the Apache Arrow integration code available to developers via GitHub. Download RAPIDS and Kinetica from the NVIDIA GPU Cloud.
- Open Source Github Repository: Kinetica UDF Python API
- Technical Blog: Working with RAPIDS Using Kinetica’s pyGDF Open Source API
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Kinetica helps many of the world’s largest companies solve some of the world’s most complex problems, including Citibank, GSK, OVO, Softbank, and Telkomsel, among others. The Kinetica Streaming Data Warehouse combines historical and streaming data analysis with powerful location intelligence and AI in a single platform, all easily accessible via API and SQL, for instant results. Organizations across automotive, energy, telecommunications, retail, healthcare, financial services, and beyond can load and analyze their entire collection of data simultaneously, delivering instant insight. Kinetica has a rich partner ecosystem, including Dell, HP, IBM, NVIDIA, and Oracle, and is privately held, backed by leading global venture capital firms Canvas Ventures, Citi Ventures, GreatPoint Ventures, and Meritech Capital Partners. For more information and to try Kinetica, visit kinetica.com or follow us on LinkedIn and Twitter.