The IBM DataStage® family of products offers industry-leading data integration to provide real-time 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. It can be deployed on hyperconverged systems such as IBM Cloud Pak® for Data, as a managed serviced 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, transfer 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.