Cask Big Data Sandbox Offered on AWS Marketplace

A new offering on the AWS Marketplace provides a sandbox for users to evaluate the flagship Big Data platform from Cask.

That platform, the Cask Data Application Platform (CDAP), can now be easily set up for testing and evaulation with the new Cloud Sandbox for AWS, which provides a single-node instance of the CDAP that's functionally equivalent except for a scaling limitation.

The sandbox is based on CDAP 4.2, released earlier this month with support for Apache Spark 2.x and better functionality for reusing existing Spark code for new applications, among other updates.

Cask said the new sandbox simplifies the evaluation process of the platform, as users don't have to set up a Hadoop cluster to use it.

The AWS offering is basically the same as the company's CDAP Local Sandbox that's run on individual on-premises machines. It bundles the CDAP SDK, runtime, CDAP UI and CDAP CLI (command-line interface) along with tools and examples.

If use of the sandbox results in a production-ready application, Cask said it can easily be moved to a distributed CDAP environment, like the Amazon EMR (Amazon Elastic MapReduce) service.

"Users can also access Cask Market from the instance that has a lot of readily available, out of the box capabilities to experience CDAP," the company's Derek Wood said in a blog post. "We have added a number of AWS specific integrations and made them available in Cask Market -- plugins to read from S3 buckets, plugins read/write to Redshift and a plugin read from Snowflake."

Company CEO Jonathan Gray also weighed in, saying, "It is no secret that the path to extracting value from Big Data investments has been a long and rocky one for many companies. Onboarding even skilled engineers new to Hadoop, setting up a proper distributed computing environment, and dealing with the integration of multiple Big Data technologies and tools have taken a big toll on the pace with which users ramp up their Big Data projects. With the new Cloud Sandbox, CDAP users can be productive developing Big Data solutions within minutes rather than being concerned about installation and configuration questions."

About the Author

David Ramel is an editor and writer for Converge360.


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