What we offer
IBM’s data integration solutions provide a full set of highly scalable capabilities, transforming data in any style and delivering it to any system.
Capabilities are built on a massively parallel processing architecture and can accommodate small and ‘big’ data volumes. Multiple delivery options are available, including bulk/batch (via ETL, ELT or mixed/TELT), incremental (data replication), and virtual (federated).
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What’s new in IBM InfoSphere Information Server 9.1
Makes high-quality information accessible, usable and manageable in new ways within a highly scalable, secure and robust data integration platform.Get the white paper
Anywhere integration with IBM InfoSphere DataStage v9.1
Enables users to design once and deploy anywhere, improves performance and provides greater integration agility – while keeping costs low.Get the brief
InfoSphere Data Replication
Delivers outstanding capabilities for loading real-time information into a data warehouse or operational data store, which can help organizations enhance business agility and visibility into key processesGet the brief
IBM InfoSphere Information Server for IBM Pure Data
Delivering tight connectivity to speed time-to-valueGet the data sheet
InfoSphere Information Server for Data Integration
Spend 3 minutes and learn how InfoSphere Information Server supports big data integration, agile integration for all levels of data volume, easy self-service data integration, and more!
Boost Data Veracity with IBM InfoSphere Data Replication
See how IBM InfoSphere Data Replication can seamlessly replicate data to and from your data warehouses
Magic Quadrant for Data Integration Tools
IBM is a leader in Gartner's Magic Quadrant for Data Integration Tools, positioned Highest in Ability to Execute
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Critical Capabilities: Data Delivery Styles for Data Integration Tools
Together with Gartner's "Magic Quadrant for Data Integration Tools," this report will help IT leaders pick the tool best suited to their conventional and emerging data delivery needs.
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Who's afraid of the big (data) bad wolf?
Shows the value of implementing information integration and governance from the very start of all types of big data projects - whether those projects focus on big data applications, data warehouses or data warehouse augmentation initiatives or involve Hadoop.
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Integrating and governing big data
Does big data spell big trouble for integration? Not if you follow these best practices
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