Datastage version 8.5, 8.7 and 9.1 Differences

Below table gives the differences between Datastage versions:

Versions	Datastage v8.5	Datastage v8.7	Datastage v9.1
New Java Integration Stage added	Doesn’t Exist	Doesn’t Exist	Supports Java code and creates baseline for upcoming big data source support.
New Unstructured text stage added	Doesn’t Exist	Doesn’t Exist	Excel read capabilities on all platforms with rich features to support ranges, multiple worksheets and New Unstructured data read.
DBMS Connector Boost	Doesn’t Exist	Doesn’t Exist	New big buffer optimization which has increased bulk load performance in DB2 and Oracle Connector by more than 50% in many cases.
Added Dual-stack protocol Support	Doesn’t Exist	IPv6 Support: Information Server is fully compatible with IPv6 addresses and can support dual-stack protocol implementations	IPv6 Support: Information Server is fully compatible with IPv6 addresses and can support dual-stack protocol implementations.
Design & Runtime Performance Changes:	Implemented by Internal code change. Design and Runtime performance is better than 8.1, 40% performance improvement in job open, save, compile etc.	Improvements in Xmeta. Significant Performance improvement in Job Open, Save, Compile etc	Improvements in Xmeta. Significant Performance improvement in Job Open, Save, Compile etc
PX Engine Performance Changes	Doesn’t Exist	Improved partition/sort insertion algorithm. XML parsing performance is improved by 3x or more for large XML files.	Improved partition/sort insertion algorithm. XML parsing performance is improved by 3x or more for large XML files.
Added Stop/Reset buttons In Designer Client:	Doesn’t Exist	Stop/ Reset button added to Compile and Run buttons for the DS jobs.	Stop/ Reset button added to Compile and Run buttons for the DS jobs.
Big Data File Stage enhanced	Doesn’t Exist	Big Data File Stage for Big Data sources (Hadoop Distributed File System-HDFS).	New Enhancement on 1. The IBM Big Data Solution Integrate and manage the full variety, velocity and volume of data. 2. New Hadoop-based Big Data Support Any to Big Data. 3. Big Data Integration with DataStage.
Added Encryption Techniques	Doesn’t Exist	Encrypted because of security reasons. 1. Strongly encrypted credential files for command line utilities. 2. Strongly encrypted job parameter files for dsjob command. 3. Encryption Algorithm and Customization.	Encrypted because of security reasons. 1. Strongly encrypted credential files for command line utilities. 2. Strongly encrypted job parameter files for dsjob command. 3. Encryption Algorithm and Customization.
Interactive Parallel Job Debugging	Doesn’t Exist	Breakpoints with conditional logic per link and node. (Link -> Rclick -> Toggle Breakpoint) The running job can be continued or aborted by using multiple breakpoints with conditional logic per link and node. (row data or job parameter values can be examined by breakpoint conditional logic)	Breakpoints with conditional logic per link and node. (Link -> Rclick -> Toggle Breakpoint) The running job can be continued or aborted by using multiple breakpoints with conditional logic per link and node. (row data or job parameter values can be examined by breakpoint conditional logic)
Balance Optimization :	Balanced Optimization is that to redesign the job automatically with maximize performance by minimizing the amount of input and output performed, and by balancing the processing against source, intermediate, and target environments. The Balanced Optimization enables to take advantage of the power of the databases without becoming an expert in native SQL.	Balanced Optimization is that to redesign the job automatically with maximize performance by minimizing the amount of input and output performed, and by balancing the processing against source, intermediate, and target environments. The Balanced Optimization enables to take advantage of the power of the databases without becoming an expert in native SQL	Balanced Optimization for Hadoop.
Transformer Enhancements	Looping in the transformer, Multiple output rows to be produced from a single input row. 1. New input cache SaveInputRecord(), GetSavedInputRecord() 2. New System Variables: @ITERATION, @Loop Count, @EOD(End of data flag for last row) 3. Functions : LastRowInGroup(InputColumn) 4. Null Handling more Options.	Looping in the transformer, Multiple output rows to be produced from a single input row. 1. New input cache: SaveInputRecord(), GetSavedInputRecord() 2. New System Variables: @ITERATION, @Loop Count, @EOD(End of data flag for last row) 3. Functions : LastRowInGroup(InputColumn) 4. Null Handling more Options.	New Transformation Expressions has been added. EREPLACE: Function to replace substring in expression with another substring. If not specified occurrence, then each occurrence of substring will be replaced.
Added View Job Log in Designer client	Doesn’t Exist	New Feature has been added (Menu -> View -> Job Log). Job log is now viewed in Designer client.	New Feature has been added (Menu -> View -> Job Log). Job log is now viewed in Designer client.