Mainframe Access & Integration for Hadoop

Bridge the gap between Big Iron and Big Data

Process Mainframe data with Hadoop & Apache Spark

Shift Mainframe Data and Batch Processing to Hadoop

Syncsort’s Mainframe Access & Integration for Hadoop Solution brings together decades of mainframe expertise with state-of-the-art Hadoop capabilities to provide a painless and seamless approach to offload mainframe data and workloads:

  • Access - get mainframe data into Hadoop and Apache Spark - in a mainframe format - and work with it like any other data source!
  • Integrate - blend mainframe, legacy and Big Data sources for better business insights
  • Comply - certified with critical Hadoop ecosystem projects for security and governance
  • Simplify - take advantage of common skillsets already in your organisation, no need to hire or train new developers

Fast-Track Data Preparation & Development

Both mainframe and Hadoop skills are in high demand – bridge the gap and reduce costly, time-consuming data collection and preparation tasks:

  • Replace complex manual code (COBOL, MapReduce, Spark) with a powerful, easy-to-use graphical development environment
  • Built-in support for COBOL copybooks and mainframe record formats including VSAM, fixed, variable, packed decimal, EBCDIC and more – without coding
  • Native LDAP and Kerberos authentication support, integration with Apache Sentry and Apache Ranger, plus FTPS and Connect:Direct mainframe data transfer
  • Efficiently copy mainframe data to Hadoop or Apache Spark, while preserving its native format for compliance – no need for staging translated copies

Best Practices for Bringing Mainframe Data to Hadoop

Gain Bigger Insights and a Better Return

This free eBook will show you how to overcome the big challenges to liberate your mainframe data, and offload costly batch workloads into Hadoop – today’s Big Data analytic platform of choice.

Learn how to avoid the pitfalls with best practices and helpful tips for leveraging mainframe data with Hadoop.

Discover how to:

  • Work with mainframe data in Hadoop just like any other data source
  • Cleanse, blend & transform data on the cluster
  • Take advantage of common skillsets in your organisation
  • Secure the entire process

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