DB2 V11 Top New Features

What is new in DB2 V11 for ZO/s.

  • less CPU time on heavy insert, select query workloads, and when running queries against compressed tables.
  • Improved data sharing performance and efficiency.
  • Improved utility performance and additional zIIP off-load for LOAD and RUNSTATUS
  • Cost-effective archiving of warm and cold data with easy access to both within a single query
  • Intelligent statistics gathering and advanced optimization technology for efficient query execution in dynamic workloads.
  • Additional online schema changes that simplify management, reduce the need for planned outages, and minimize the need for REORG.
  • Productivity improvements for DBAs, application developers and system administrators.
  • Efficient real-time scoring within your existing transaction environment.
  • Enhanced analysis, forecasting, reporting and presentation capabilities, as well as improved storage management, in QMF.
  • Expanded SQL, SQL PL, temporal and XML function for better application performance.
  • Faster migration with application protection from incompatible SQL and XML changes and simpler catalog migration.
  • DB2 11 is its support of an extended RBA. Read this Robert Catterall post for a good explanation of this feature.
  • The addition of DROP COLUMN should continue to improve online schema changes. New online data repartitioning is designed to significantly reduce the need for planned outages.

See some more.

  • No application changes required for DB2 upgrades
  • DB2 11 also brings performance enhancements with long running BIND and DDL threads and improved clone table management and more efficient data sharing.
  • DB2 11 applications with SQL or XML will be able to run in compatibility mode, even if they’re incompatible with the new release.
  • New functionality “Index Duplicate Removal”
  • Suppress Null index- It suppress if all values are Null in Index columns
  • Good support for data analytics/integration

Refer here for more details.

Author: Srini

Experienced Data Engineer, having skills in PySpark, Databricks, Python SQL, AWS, Linux, and Mainframe