Mainframe Access and Integration

Mainframe data access into Hadoop

Get your data into Hadoop, in a mainframe format. Use Connect for Big Data to efficiently copy mainframe data to Hadoop, while preserving its native format for compliance.

Once the data is on Hadoop, Connect for Big Data is the only solution that can leverage the cluster’s distributed resources to access and integrate native mainframe data without staging translated copies.

Integrate your mainframe data – cleanse, blend and transform data on the cluster

Only Connect for Big Data can move mainframe data onto a Hadoop cluster without modifying it from its original format and make it distributable so you can store and process it with on Hadoop.

You can even process it directly with MapReduce and Spark for greater parallelization and improved performance when working with mainframe variable data on the cluster.

Bridge the skills gap – our easy-to-use interface means there’s no need to understand COBOL, MapReduce or Spark

Save the time and expense of hiring COBOL, MapReduce or Spark specialists. Plus, avoid the learning curve that comes with new languages and complex tools.

With its design once, deploy anywhere approach,, Connect for Big Data bridges the skill gap. It takes only a basic understanding of data integration to design jobs and tasks for data ingestion, translation and transformation and run them under any framework.

Secure the entire process with smarter security

Mainframes house some of the most sensitive data in an organization, so security is critical for any solution that accesses that data. Connect for Big Data supports your security and compliance needs with:

• Support for FTPS and Connect:Direct data transfers
• Native Kerberos and LDAP support
• Integration with common security systems such as Apache Sentry
• The ability to access and work directly with mainframe data in its native format – preserving data lineage for governance mandates