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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Flexibility to execute your data pipelines wherever your data resides - in any region, on-premises, cloud, or hybrid cloud..
Simplify building pipelines on a no/low code UI with hundreds of pre-built native connectors and transformations so that any user can deliver high quality data.
Scale data transformation with built-in parallel processing and DataOps, reducing inception to production time.
Interoperability with IBM Data Fabric offerings provide an integrated approach to data management including quality, lineage, and governance from a single interface.
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 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 SaaS
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.
Work with your peers on DataStage flows and control access to your projects.
Efficiently perform data integration work in a no-code or low-code environment with a user-friendly interface. Hundreds of prebuilt functions and connectors reduce development time and improve consistency of design and deployment.
DataStage has a best-in-breed, highly scalable parallel engine that processes substantial data volumes. Built-in auto workload balancing provides high performance and elastic management of compute resources.
Accelerate DataOps with shared platform connections and integrations with other products in IBM Cloud Pak for Data, including data virtualization, governance, business intelligence and data science services.
"Datastage is a powerful tool that allows us to define ETL / Data Integration processes in a very simple way. It allows us to integrate data from multiple sources and coordinate the ETL processes in a single tool."
"Overall experience is good. I have been working with Datastage since last 5 years. The tool is easy to learn and has a wide variety of options to transform data. The version upgrade was simple, it was easy to deploy entire projects across different environments."
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