Businesses leverage data replication to efficiently manage data growth with trusted data integration and synchronization. It powers the use of real-time information for DataOps by enriching big data systems and mobile applications, even capturing data that is constantly changing.
The IBM data replication portfolio supports high volumes of data with very low latency, making the solution ideal for multisite workload distribution and continuous availability — whether across the data center, from on premises or to the cloud. This robust support for sources, targets and platforms ensures the right data is available in data lakes, data warehouses, data marts and point-of-impact solutions, while enabling optimal resource utilization and rapid ROI.
Leverage high-performance capabilities, for integration with Kafka and Hadoop.
Data is captured directly from database logs for dynamic delivery to data lakes.
Replicate and synchronize operations to a backup system for continuous availability.
Support big data integration, continuous availability, consolidation and business analytics.
Deliver data changes for data warehouses, quality processes and IBM Master Data Management systems.
Capture changes to nonrelational mainframe data and deliver them to relational databases.
Get flexible and near real-time integration of all types of data both on premises and on the cloud with a scalable ETL platform.
Flexibly meet your unique requirements — from data integration to data quality and data governance.
Hear how you can benefit from the latest data replication technologies.
Learn how to perform high-volume, secure data replication across heterogeneous data stores in this solution brief.
Deliver transactional data to your Hadoop and Kafka-based data lakes or data hubs in near real-time. See how in our solution brief.
See how easy it is to replicate changes in IBM Db2® for z/OS® data down to Kafka topics in the IBM Cloud®.
Discover how data replication can help you get the most out of your unstructured and structured data in this blog post.