IBM Mainframe z Series Hadoop Spark Integration for Big Data
IBM z mainframe software that extracts mission critical z Series data sources like VSAM files, DB2 data, fixed and variable z/OS files for Big Data Analytics and archiving on Hadoop or Spark, making the massive volumes of z/OS data available for business analysts to make more informed decisions. COBOL Copybooks can be directly mapped to your IBM z mainframe data. Compared to IBM z Series storage costs, Big Data solutions serve as a very low cost alternative, while providing priceless business insights. IBM mainframe data extracted is preserved exactly as it was on the z Series for regulatory compliance. Using an intuitive GUI, implementation is completed without any MapReduce, COBOL or Hadoop programming, and only takes days for IBM z to Big Data analytics to be completed. High performance workflows on Hadoop or Spark can be accomplished without any coding or tuning.
Connectivity: FTPS, Connect:Direct, Hive, Impala, HDFS, ORC, Avro, Parquet Kudo, Kafka, MapR Streams
File Formats: DB2, VSAM, Mainframe Fixed, Mainframe Variable and Fujitsu
Format Conversions: EBCDIC ACII, Packed Decimal COMP-1, COMP-2 and COMP-3
Security: FTPS and Connect:Direct, Native Kerberos, LDAP Security, Apache Ranger, Apache Sentry integration
Features at a glance
- Exports IBM z mainframe data into Hadoop or Spark in a z Series format, but seen like other data sources
- Preserves your IBM mainframe data exactly as it was on the mainframe
- Enable non-mainframe developers to work with native mainframe data on the cluster
- Cleanse, blend & transform data on the cluster
- Directly access and understand VSAM files, mainframe fixed & variable files, and DB2 data
- Give your data meaning with COBOL Copybooks mapped directly to the mainframe data
- Stop wasting weeks of development time just to understand the data
- Easily and securely connect to the mainframe with FTPS and Connect: Direct
- Leverage native Kerberos and LDAP support, as well as certified integration with common security systems such as Apache Ranger and Apache Sentry.
- Use a simple GUI to bridge the gap between mainframe and Hadoop skills availability – developers don’t need to understand COBOL, MapReduce or Spark
