BlazingDB Blog Welcome to BlazingSQL Notebooks

Sign In and Write Code on GPUsBlazingSQL Notebooks is a fully managed, high-performance JupyterLab environment, with an always attached GPU, and preinstalled GPU-accelerated data science packages from the RAPIDS ecosystem.BlazingSQL Notebooks provides the fastest and easiest way to get started with the RAPIDS stack. You can read on to learn more or simply create a user by signing in. Never has it been easier to start writing code on GPUs.What can you do?In a nutshell, you can run RAPIDS, or complete data science workloads on GPUs.BlazingSQL Notebooks maintains a series of environments that optimized for performing end to end analytical workloads entirely on GPUs. Notebooks does this through the use of a series of core open-source projects.Each of these projects is fundamental for the high-performance notebook experience.Jupyter: BlazingSQL Notebooks uses JupyterHub to spawn isolated JupyterLab servers so users can have a comfortable and secure web IDE for data science.RAPIDS: A suite of libraries mirrored after some of the most popular Python packages for running end to end analytics on GPUs.BlazingSQL: A Pythonic SQL engine built on the same GPU primitives underlying the RAPIDS ecosystem.Dask: A package for natively scaling Python, which simultaneously enables BlazingSQL and other RAPIDS packages to scale from one to many GPUs and servers.BlazingSQL Notebooks has two, continually updating, Python environments:RAPIDS Stable — rarely updated, mostly on significant releases (every 4–6 weeks), and some hotfixes.RAPIDS Nightly — receives multiple updates each week after testing a series of demo notebooks.Why we built thisBlazingSQL helped build the RAPIDS ecosystem to support our vision of creating an open-source Python SQL engine that provides an ETL bridge to GPU-accelerated data science.With our experience deploying data science GPU clusters, we decided to create a seamless experience where users could start writing their first GPU-accelerated code in a matter of seconds.Now begin writing GPU-accelerated code for analytics with the RAPIDS stack using our easy to follow introductory notebooks!The DataFrameData VisualizationMachine LearningWelcome to BlazingSQL Notebooks was originally published in BlazingSQL on Medium, where people are continuing the conversation by highlighting and responding to this story.