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Overcome your Big Data integration, migration, cleansing and transformation challenges with Syncsort

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Collect, Prepare, Blend, Transform & Distribute Data Seamlessly with Syncsort’s DMX-h

Break free from Hadoop complexity! Syncsort’s DMX-h is specifically designed to remove barriers to mainstream Hadoop adoption and deliver the best approach for shifting heavy workloads from expensive data warehouses and mainframes into Hadoop.

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Solution Sheet

DMX-h

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Solution Sheet

Ironstream

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Solution Sheet

Trillium Quality for Big Data

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Read our latest eBook

Bridging the Gap Between Big Iron & Big Data

Today’s circuitous path of exporting mainframe data and importing it into Hadoop isn’t just complicated, but it’s a huge hassle that has extreme time and cost implications. These have discouraged organizations from using mainframe data for Big Data and other analytic purposes. Mainframes power many mission-critical applications throughout the enterprise – collecting, generating and processing some of the largest data volumes with exceptional performance and reliability.

This eBook will guide you through the process of overcoming the four biggest challenges of leveraging mainframe data, and explain how to offload costly batch workloads from the mainframe onto today's Big Data technologies. You will also learn useful tips and best practices on bridging the gap between Big Iron and Big Data and achieving massive data scalability with Hadoop.

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Customer success story

PagesJaunes uses Syncsort DMX-h for the extraction, transformation and loading (ETL) of data into Hadoop – combining robustness and performance both in response times and volume of data.

To help face technical challenges from an explosion in data volume, storage of unstructured data, and real time reporting, PagesJaunes employed a Big Data strategy focused on moving to the Cloudera Hadoop framework from IBM Netezza, allowing their commercial teams to make the right decisions quickly.

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