IBM says it is making it easier and faster for organizations to access and analyze data in-place on the IBM z Systems mainframe with its new z/OS Platform for Apache Spark.
By enabling Spark, an open source analytics framework, to run natively on the z/OS mainframe operating system, IBM says, data scientists can analyze data in place on the system origin, without the need to extract, transform and load (ETL) by breaking the tie between the analytics library and underlying file system.
IBM also announced it is working with three partners, DataFactZ, Rocket Software, and Zementis, to create customized solutions using IBM z/OS Platform for Apache Spark.
z Systems still handles critical data and transactions for many of the world’s major banks, insurers, retailers and transport companies. With the new platform for Spark, organizations can now leverage these capabilities, applying advanced in-memory analytics through Spark without moving data off the mainframe, thereby helping to reduce effort, cost, and risk. The IBM z/OS Platform for Apache Spark includes Spark open source capabilities consisting of the Apache Spark core, Spark SQL, Spark Streaming, Machine Learning Library (MLlib) and Graphx, combined with a mainframe-resident Spark data abstraction solution.
Developers and data scientists can use their existing expertise with programming languages such as Scala, Python, R and SQL to accelerate time to value for insights. In addition, optimized data abstraction services remove complexity, providing access to enterprise data in traditional formats such as IMS, VSAM, DB2 z/OS, PDSE or SMF with familiar tools via Apache Spark APIs.
To learn more about the IBM z Systems portfolio, visit www.ibm.com/systems/z/.