Anaconda's Python-based analytics hit the enterprise with new subscription plans
Launched at Strata + Hadoop World in New York, the enterprise version of Anaconda is designed to enable corporate data science teams and in-house developers to explore and solve complex data problems in a packaged, easy-to-deploy, open data science stack.
The software offers easy GPU and multicore integration, Continuum said, along with scalable browser-based visualization via data shading. Also included is a framework that insulates the organization from back-end changes and allows users to write data and analytic queries once and then deploy them anywhere.
The open version of Anaconda is now freely available under the BSD license, allowing it to be fully redistributed without attribution. For organizational users, paid versions are available in three subscription tiers: Pro, Workgroup and Enterprise, beginning at $10,000 per year for up to 10 users with support and indemnification.
Included in Anaconda subscriptions are exploration and visualization features, notebook publishing and sharing, full cluster support, integration with Spark and Hadoop, and scalable, real-time big data visualization.
Anaconda's customers include more than 200 of the Fortune 500, 19 of the Fortune 25 and 8,000 universities around the world, Continuum says, including Boeing, Procter & Gamble, Pepsi, Schlumberger, the U.S. Department of the Treasury and the Securities and Exchange Commission.
Anaconda Cloud, meanwhile, offers a free, publicly available Web portal for the Anaconda Community to share notebooks, packages and reproducible environments. It also includes a download for cluster prototyping of analytics that scale to big data. Private plans on Anaconda Cloud cost $9 per month.
In other Python news, Teradata on Monday announced the new, open-source Teradata Module for Python, which aims to help software developers create DevOps-enabled applications that leverage data in the Teradata warehouse. The release makes Teradata the first vendor to extend DevOps practices to the multi-application data warehouse environment, it said.