Wallaroo Labs Announces Open-Source Version of Wallaroo

Big Data Engine Provides "Serverless" Features and Breakthrough Simplicity for Python
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Wallaroo Labs (formerly Sendence) today announced the open-source version of Wallaroo, a highly elastic data processing engine for building and operating big data, fast data, and machine learning applications.

Wallaroo supports Python natively, unlike Apache Spark and Storm. It leverages existing business algorithms, avoids costly and time-consuming migrations to Java, and simplifies application deployment. Wallaroo's "serverless" features make the infrastructure virtually disappear, delivering rapid time-to-market, very low operating cost, and live applications that can grow and shrink capacity on demand.

"We are delighted to offer Wallaroo to the open-source community," said Vid Jain, Founder and CEO, "and early response to the release has been overwhelmingly positive. We are looking forward to building a robust community of developers and data scientists."

"Developers struggle because the tools available to quickly build prototypes on laptops don't work well in production environments, and the production tools available weren't designed for rapid application iterations. Wallaroo solves this problem by providing a single processing framework supporting developers from prototype to production anywhere, without changing a line of code," said Sean Allen, V.P. Engineering, and author of Applied Storm.

Using Wallaroo is as easy as 1) writing business algorithms and integrating data via an API, 2) bundling your code with Wallaroo and deploying to any cluster, whether on-premise or in the cloud, and, 3) achieving fast results as Wallaroo spreads data and processing over any number of servers.

Wallaroo is available at http://www.wallaroolabs.com/community, with full documentation, examples, and tutorials as well as the link to the GitHub repository.

About Wallaroo Labs

Wallaroo Labs (formerly Sendence) makes Wallaroo, the open-source, highly elastic processing engine for deploying big data, fast data, and machine learning applications in native Python (and more). It requires no Java, unlike Apache Spark, so it's much simpler. And Wallaroo makes the infrastructure virtually disappear so you get rapid time-to-market, very low operating cost, and live applications that can grow and shrink capacity on demand.

To get a demo or talk to us about your specific application, contact us at info@WallarooLabs.com

Media Contact:
Chuck Blake
Phone: (646) 801-3168
Email: chuck@wallaroolabs.com

Source: Wallaroo Labs

About Wallaroo Labs

Wallaroo makes the infrastructure virtually disappear so you get rapid deployment, very low operating cost, and elastic capacity with zero downtime for your applications in surveillance, data analysis, machine learning, and microservices.

Wallaroo Labs
222 Broadway, co WeWork
New York, New York
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