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IBM DataStage

Score7.7 out of 10

42 Reviews and Ratings

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What is IBM DataStage?

IBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.

Categories & Use Cases

Key Features

Learn about the best (and worst!) features IBM DataStage has to offer, as determined by TrustRadius' reviewers.
Based on 42 ratings of IBM DataStage's features
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Top Performing Features

  • Connect to traditional data sources

    Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications

    Category average: 8.8

  • Simple transformations

    Simple data transformations are calculations, data type conversions, aggregations and search and replace operations

    Category average: 8.8

  • Connecto to Big Data and NoSQL

    Ability to connect to non-traditional data sources like Hadoop and other big data technologies, and NoSQL databases

    Category average: 7.6

Areas for Improvement

  • Integration with data quality tools

    Integration with tools for cleansing, parsing and normalizing data according to business rules

    Category average: 7.2

  • Integration with MDM tools

    Integration with master data management tools to ensure data consistency across the organization

    Category average: 7.1

  • Metadata management

    Automated discovery of metadata with ability to synchronize and share metadata with other tools like Master Data Management

    Category average: 7.4

Reviews

What users are saying about IBM DataStage.
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IBM InfoSphere DataStage Review

Incentivized
Filippo OrlandoView profile
Data Analyst | Data Developer - Advanced Analytics in Information Technology at Unieuro S.p.A. (1001-5000 employees employees)

Pros

  • reliability
  • capillarity

Cons

  • complexity
  • adaptability

Return on Investment

  • complex to integrate and adapt
  • reliable and safe for traditional flows

Alternatives Considered

Talend Open Studio, Informatica Integration Cloud and KNIME Analytics Platform

Other Software Used

KNIME Analytics Platform, Talend Open Studio, Qlik Sense, QlikView

Datastage general overview.

Verified User
Administrator in Information Technology (51-200 employees employees)

Use Cases and Deployment Scope

It handles large business scale data. Since this an example of ETL software, it can handle large amount of data records especially banking information to our clients, migrating and generating them into new sets of information that we can utilize into a better tangible data for processing. It can generate alot of information based on a lot data dump that we can utilize for more business refined approach.

Pros

  • Executing batch jobs (datastage jobs).
  • Compiles a lot of datasets into a new set of information.
  • It creates more refined information based on what we create and define from the job logics created.

Cons

  • Parameter refreshes the variables that need to be refreshed all the time when a new job is deployed.
  • Defining variables one by one takes a lot of time especially those are hard coded.
  • Jobs are sometimes get hung.
  • Sessions locks up the jobs.

Return on Investment

  • It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
  • Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
  • Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.

Usability

Other Software Used

ACE, IBM Instana

Good ETL tool

Incentivized
Verified User
Manager in Information Technology (1001-5000 employees employees)

Use Cases and Deployment Scope

IBM DataStage is use as a ETL tool useful to extract information from the source systems (for example SAP ERP), to trasform them defining the correct logics to calculate KPIs and clean data (Data Quality checks). Morever it is used to read manul file from Business Users and to link them into the useful information for the BI tool.

Pros

  • Easy to use, you can manage both visual joins and transformation and SQL queries
  • Able to read from all source systems, there are all the needed connectors
  • It can orchestrate job at different levels and it is easily scalable

Cons

  • Many specific parameters are not well documented and therefore are difficult to use
  • The debugging option doesn't work well
  • datatype management is complex

Return on Investment

  • Centralization of ETL processes in one tool
  • All the flows are updated overnight and reports ready for Business Users in the morning
  • Using SAP ERP connector , we avoid using a middleware

Usability

Alternatives Considered

Matillion, SAP Data Services, Oracle Data Integrator (ODI), SQL Server Integration Services, dbt and AWS Glue

Other Software Used

Snowflake, MicroStrategy Analytics, Microsoft Power BI

Master of Data Mapping and Cloud Data Management IBM Platform.

Incentivized
Edger LoredoView profile
Project Manager in Engineering at Keyway (11-50 employees employees)

Use Cases and Deployment Scope

The effective mapping product and highly effective for project data management and scalability is the best. Functions are simple to start with and all the features are easy to custom. The IBM platform offers the best mapping capability and the data modeling functions are excellent. The reports are excellent and effective.

Pros

  • Mapping tools are excellent.
  • Reporting functions.
  • Data collaboration.

Cons

  • The deep functions manipulation is tricky.
  • Tools are not easy to manipulate through Cloud services.
  • Ability to manage big data can be more functional.

Return on Investment

  • Great data mapping solution and easy to assemble various data report.
  • Excellent analytics production and easy to visualize big data.
  • Easy project management and reliable integration platform and Cloud data management.

Alternatives Considered

Micro Focus Storage Manager, Azure Cost Management and Microsoft Exchange Online Archiving

Other Software Used

Micro Focus ALM / Quality Center, IBM Cloud for VMware Solutions, Google Cloud Dataflow

IBM Inforsphere datastage review

Incentivized
niman goliView profile
Storage Lead in Sales at DXC Technology (10,001+ employees employees)

Use Cases and Deployment Scope

IBM InfoSphere DataStage is used for data analysis for business trending and banking aging report for the customers.It would be helpful for finding when the last transaction was done and when the future transaction would be coming for . IBM InfoSphere DataStagecan help with ease of access , easy of gui management and easy navigation for the user to great help

Pros

  • banking environment
  • user data management
  • user account management

Cons

  • data stage integration with cloud
  • integration with bmc
  • database management with datastage

Return on Investment

  • its best on return on investment
  • its comes at low cost
  • its easy of use access

Alternatives Considered

BMC Cloud Lifecycle Management

Other Software Used

BMC Automated Mainframe Intelligence (AMI), Dell EMC AppSync, Hitachi Compute Blade (BladeSymphony)