Transactional data is the definitive source of truth and represents the current state of the business for many organizations. This highly valuable IBM Z® data, combined with other lakehouse data, can provide unique predictive value for artificial intelligence (AI) insights.
Seamlessly synchronize valuable enterprise IBM Z data to your IBM® watsonx.data™ lakehouse to unlock the power of mainframe transactional data for AI, by using the most up-to-date transactional data in machine learning or AI models.
- Reduce time for accessing and analyzing mainframe data with a revolutionary simplified approach to synchronizing mainframe data.
- Apply as much compute to a complex analysis as you want and need without impacting operational applications.
- Support cloud-based lakehouse initiatives with reduced cost and effort.
- Synchronize IBM® Db2® for z/OS®, IMS and VSAM data to the Iceberg open table data format in watsonx.data.
The IBM z Integrated Information Processor (zIIP) enabled approach to synchronize IBM Z data with watsonx.data.
Purpose-built to deliver data originating from the mainframe for access in IBM watsonx™.
Provides the most current IBM Z data with reduced resource consumption and workload isolation.
Data Gate for IBM watsonx provides a simple, zIIP-enabled, highly optimized, purpose-built, unidirectional, resilient, standardized approach for synchronizing data from IBM Z.
Engineered as part of Db2 for z/OS and watsonx.data to simplify integrating transactional mainframe data within traditional machine learning and generative AI applications.
Bring valuable enterprise data into a watsonx.data lakehouse.
Synchronize IBM Z® data to the cloud for modern data architectures.
Unlock the power of transactional mainframe data for AI through integration with IBM Data Gate for watsonx.
Radically simple, ultra-efficient IBM Z data synchronization to the cloud.
Scale analytics and AI workloads, for all your data, anywhere with watsonx.data, the industry’s data store that is open, hybrid and governed.
Handle rapidly changing, diverse and unpredictable workloads while optimizing resource use and investment.