IBM® DataStage® products offer industry-leading real-time data integration for access to trusted data across data lakes and multicloud and hybrid cloud environments for AI. Real-time analytics is now easier than ever, with a cloud-native architecture built on containers and microservices and a best-of-breed parallel engine. DataStage solutions can be deployed on hyperconverged systems such as IBM Cloud Pak® for Data, as a managed service on IBM Cloud®, or on premises.
IBM DataStage on IBM Cloud Pak for Data allows you to simplify operations by automating and accelerating administration tasks to reduce total cost of ownership (TCO) and meet business service-level agreements (SLAs). Avoid vendor lock-in by deploying on any cloud or multicloud environment, and leverage industry-leading security, reliability and scalability from Red Hat® OpenShift®.
Accelerate DataOps and AI innovation through automated integration templates and seamless out-of-the-box integration with governance, BI, data virtualization and data science services with IBM DataStage on IBM Cloud Pak for Data.
Design once, run anywhere with built-in workload balancing, parallelism and dynamic scalability
Separate the design from the runtime to run remote jobs where your data resides. A parallel engine optimizes extract, transform and load (ETL) performance, and automatic load balancing maximizes throughput while scaling with your data volumes.
Automated delivery pipelines to release jobs to production
Container-based integration components along with git-based source control tooling allow for automation of CI/CD pipelines for jobs from dev to test to production.
User-friendly design with infused ML capabilities and rich set of connectors and transformations
IBM DataStage Flow Designer, with infused machine learning capabilities, built-in search and prebuilt connectors and transformations, allows you to quickly create and run DataStage jobs and connect with governance.
In-flight data quality and data security for trusted data delivery
Automatically resolve quality issues using IBM InfoSphere® QualityStage® when data is ingested by target environments such as data lakes. Provide metadata support for policy-driven access to sensitive data.