Making Big Data Elastic with the SnapLogic iPaaS

SnapReduce 2.0The theme of the week at SnapLogic has been all about elastic big data after our announcement of SnapReduce 2.0, which enables SnapLogic to run natively on Hadoop as a YARN-managed resource that elastically scales out to power next generation analytics. If you missed the news, SnapReduce 2.0, accessible via our Early Access Program here, delivers:

  • Improved Big Data Acquisition: Instantaneous access to more than 160 data sources from within Hadoop via pre-built connectors, called Snaps. Going beyond developer tools like Sqoop and Flume, SnapLogic allows Hadoop users to access and introspect cloud and on-premises data sources in an easy-to-use graphical interface. Updates to the SnapLogic Hadoop Distributed File System (HDFS) Snap also take advantage of Hadoop 2.0 innovations.
  • Double Data Scientist Productivity: Most data scientists spend the majority of their time on cumbersome coding tasks, data gathering and data preparation. SnapReduce 2.0 doubles data scientist productivity by simplifying complex data shaping tasks such as transformations, joins and unions.
  • Universal Big Data Delivery: Make Hadoop data and analytics results easily available to off-cluster applications and data stores such as statistical packages and business intelligence (BI) or visualization tools.

Here are some additional resources and details about SnapReduce and making big data elastic:

And finally, don’t forget to access our starter kit for elastic integratioElastic Integration Toolkitn, which contains everything you need to know about big data and cloud integration. There are plenty of valuable resources that reflect on what our CEO Gaurav Dhillon recently said:

To deliver on the promise of big data, enterprise IT organizations must respect data gravity and ensure that data processing is as close to its storage as possible.


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