This article explores the enterprise analytics market, use of Apache Spark on IBM z Systems platforms, integration between Apache Spark and other enterprise data sources, and IBM’s new offering for Machine Learning on z/OS.
My introduction to DB2 and SQL occurred over 30 years ago. It changed my life. Now big data tools have SQL as well.
Until recently, this ACID compliancy wasn’t fulfilled by Hadoop transactions, but the advent of Hive 2 (June 2016) and others has changed this. Now you can have an equally valid acidity on Hadoop as you would expect on DB2.
This brings up once more the question on the relevance of DB2.
DB2 for z/OS is no longer about the traditional relational structured data only. The evolution brought us not only binary objects, or XML and JSON, but also other non-structured data living in a distributed file system such as HDFS.
Apache Spark has become a hot topic in the world of Analytics. It is seen as a better performing alternative to Map/Reduce , and as a means to do analytics combining data across a wide set of data sources. This video is a excellent introduction to what Spark is, and how it works with DB2 for z/OS.