Use all your data with a data fabric
Discover the new features IBM® Data Fabric offers
Overview
Multicloud, AI-powered data integration
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 cut 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.
Clear data roadblocks with DataStage on IBM Cloud Pak for Data (01:53)
What is DataStage for IBM Cloud Pak for Data?
What is IBM Cloud Pak for Data? This cloud-native insight platform — built on the Red Hat® OpenShift® container orchestration platform — 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 the 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.
How much can you save by upgrading?
Take the business value assessment to see the savings with DataStage for IBM Cloud Pak for Data.
Features
Full spectrum of data and AI services
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.
Parallel engine and automated load balancing
Process data at scale by optimizing ETL performance with a best-in-breed parallel engine and load balancing that maximizes throughput.
Metadata support for policy-driven data access
Protect sensitive data with metadata exchange using IBM Watson® Knowledge Catalog. Use data lineage to see how data flows through transformation and integration.
Automated delivery pipelines for production
Automate continuous integration/continuous delivery (CI/CD) job pipelines from dev to test to production and help reduce development costs.
Extensive set of prebuilt connectors and stages
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.
IBM DataStage Flow Designer
Increase developer productivity with machine learning-assisted design in a user-friendly interface, helping cut development costs.
In-flight data quality
Trust data delivery using IBM InfoSphere® QualityStage® to automatically resolve quality issues when data is ingested by target environments.
Automated failure detection
Reduce infrastructure management effort 65% - 85%², letting users focus on higher value tasks.
Distributed data processing
Execute cloud runtimes remotely wherever the data resides, while maintaining data sovereignty and minimizing costs.
Deployment options
As a service
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.
On premises or any 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.
On premises
Run basic ETL jobs on premises using IBM DataStage on IBM Cloud Pak for Data as a Service. Parallel processing and enterprise connectivity deliver a scalable platform.
Modernize your existing capabilities with IBM DataStage for IBM Cloud Pak for Data — AI-powered data delivery, anywhere
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Collaborate
Collaborate
Work with your peers on DataStage flows and control access to your projects.
Build data pipelines
Build data pipelines
Efficiently perform data integration work in a no-code/low-code environment with a user-friendly interface. Hundreds of prebuilt functions and connectors reduce development time and improve consistency of design and deployment.
Auto workload balancing
Auto workload balancing
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.
Connections, integration
Platform connections and integration points
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.
Client stories
Wichita State University
HUK-Coburg
Testimonials
DataStage on SaaS and IBM Cloud Pak for Data delivers ultimate flexibility – data movement and transformation on a modern, hybrid cloud architecture with seamless integration into IBM’s data fabric ecosystem.
Kevin Burnley,
Director, Technical Sales EMEA
Mastech InfoTrellis
Working with DataStage for IBM Cloud Pak for Data, we’ve transformed advanced analytics using open and transparent methodologies.
Philip Black,
Vice President, Client Services, TechD
What’s new
IBM ranks second highest in the Data Fabric Use Case
See why in the 2021 Gartner Critical Capabilities for Data Integration Tools.
How to get more from IBM DataStage
Learn how to improve productivity by connecting to new sources and targets more quickly when building ETL jobs.
IBM is a Leader
See why in the Gartner 2021 Magic Quadrant for Data Integration Tools.
Related products
IBM Cloud Pak for Data
An open, extensible data and AI platform that runs on any cloud
IBM InfoSphere® Information Server Enterprise Edition
An end-to-end data integration platform to help you cleanse, monitor, transform and deliver quality data
IBM InfoSphere® Information Server for Data Integration
A tool to extract and transform data in any style and load the data into any system
Get started with IBM DataStage
¹ Forrester, New Technology: The Projected Total Economic Impact Of IBM Cloud Pak For Data (PDF, 1.3 MB), February 2020