IBM® DataStage® is an industry-leading data integration tool that helps you 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, but to reduce data integration time and costs, upgrade to DataStage for IBM Cloud Pak® for Data and experience powerful automated integration capabilities in a hybrid or multicloud environment.
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IBM Cloud Pak for Data is a cloud-native insight platform built on the Red Hat® OpenShift® container orchestration platform. It integrates the tools needed to collect, organize and analyze data within a data fabric architecture. It dynamically and intelligently orchestrates data across a distributed landscape, to create a network of instantly available information for data consumers. IBM Cloud Pak for Data can be deployed on-premises, as a service on IBM Cloud® or on any vendor’s cloud.
DataStage is available as an add-on to an IBM Cloud Pak for Data software license or as a service through IBM Cloud Pak for Data as a Service.
Execute ETL and ELT Pipelines in any Cloud, Data Center or On-premises.
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Run workloads 30% faster with workload balancing and a parallel engine.¹
Bring data integration to your data. Design jobs once and move runtimes to where data resides.
Extend capabilities while preserving existing DataStage investments.
Use governance capabilities on IBM Cloud Pak for Data.
Manage the data and analytics lifecycle on the IBM Cloud Pak for Data platform. Services include data science, event messaging, data virtualization and data warehousing.
Process data at scale by optimizing ETL performance with a best-in-breed parallel engine and load balancing that maximizes throughput.
Protect sensitive data with metadata exchange using IBM Watson® Knowledge Catalog. Use data lineage to see how data flows through transformation and integration.
Automate continuous integration/continuous delivery (CI/CD) job pipelines from development to testing to production and help reduce development costs.
Use prebuilt connectivity and stages to move data between multiple cloud sources and data warehouses, such as IBM Netezza® and IBM Db2® Warehouse on Cloud.
Increase developer productivity with machine learning-assisted design in a user-friendly interface, helping cut development costs.
Trust data delivery using IBM InfoSphere® QualityStage® to automatically resolve quality issues when data is ingested by target environments.
Reduce infrastructure management effort by 65% - 85%, allowing users to focus on higher-value tasks.²
Execute cloud runtimes remotely wherever the data resides, while maintaining data sovereignty and minimizing costs.
Access all the latest capabilities available as part of IBM DataStage on IBM Cloud Pak for Data as a Service, a subscription model for a set of integrated services fully managed on IBM Cloud.
Add IBM DataStage Enterprise (or IBM DataStage Enterprise Plus) to IBM DataStage on IBM Cloud Pak for Data as a Service to run workloads on-premises or on any cloud.
Run basic ETL jobs on-premises using IBM DataStage on IBM Cloud Pak for Data as a Service. Parallel processing and enterprise connectivity delivers a scalable platform.
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Footnotes
1 Workload balancing with IBM DataStage on IBM Cloud Pak for Data, November 2020
2 Forrester, New Technology: The Projected Total Economic Impact Of IBM Cloud Pak For Data, February 2020