Best Practices for Bringing Mainframe Data to Hadoop

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 skill sets 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 c

Learn more:

Free whitepaper - bridging the gap between bigg data and big iron

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