Earlier today, NVIDIA announced RAPIDS – a GPU-acceleration platform for data science and machine learning, that enables even the largest companies to analyze massive amounts of data and make accurate business predictions at unprecedented speed. We’re happy to announce that SQream has joined the RAPIDS open source initiative!
RAPIDS is customizable, extensible, and interoperable. Plus, this open-source software is supported by NVIDIA, built on Apache Arrow. RAPIDS lets data scientists execute entire data science pipelines with the help of NVIDIA GPUs.
RAPIDS builds on popular open-source projects — including Apache Arrow, pandas and scikit-learn — by adding GPU acceleration to the most popular Python data science toolchain.
Together with SQream DB’s existing capabilities, data scientists will now be able to combine the flexibility of the open-source data science tools and suites to prepare, explore, and analyze more data than ever before, with never-before seen ease-of-use. The entire suite is all in-GPU, reducing analysis and training time from days to hours.
RAPIDS lets everyone experience GPU-acceleration, with:
- Hassle-free integration with your Python data science toolchain
- Seamless scale from GPU workstations to multi-GPU servers and multi-node clusters
- Increased machine learning model accuracy by iterating on models faster and deploying them more frequently
- Drastically improved productivity with near-interactive data science
- Deployment flexibility—in the cloud or on-prem—and easy scalability from a workstation to multi-GPU servers to multi-node clusters
“The work NVIDIA has done on RAPIDS presents an exciting opportunity for dramatically speeding up the data science pipeline. By combining SQream DB’s capability of piping in very
large amounts of data into the RAPIDS data science platform, we expect that data scientists will be able to run models faster and on more data than ever before.”, said SQream’s CEO Ami Gal.