Rocket DataEdge · Change data capture
Rocket Data Replicate and Sync
Keep mainframe, distributed and cloud data continuously aligned with log-level change data capture, bidirectional synchronisation and resilient delivery—without returning to batch windows.
Talk to a consultantWhat is RDRS?
Current data, without disrupting the systems that run the business.
Continuous enterprise data replication.
Rocket Data Replicate and Sync uses change data capture to continuously move committed data changes between IBM mainframe, distributed, cloud, streaming and analytics platforms.
Unlike scheduled ETL, RDRS reads transaction logs and captures only changed records. That delivers sub-second data freshness with near-zero impact on source-system performance, while keeping connected environments consistent.
Enterprise blockers
What slows real-time data across a hybrid estate?
Modernisation stalls when current operational data cannot move reliably, economically or in a form modern platforms can use.
Mainframe CPU cost
Batch replication and on-mainframe transformation consume more capacity as data volumes grow. RDRS captures changes at log level and can move downstream processing off the mainframe.
Data latency
Scheduled extracts leave applications, dashboards and AI models working from older snapshots. Continuous CDC reduces dependence on batch windows.
Platform differences
Mainframe data formats and code pages are not natively understood by every cloud platform. Built-in translations and transformations streamline delivery.
Replication fragility
Failed jobs and custom integrations can leave systems out of sync. Restart, rollback and recovery controls help replication resume from a confirmed point.
Hybrid data silos
Operational data spans mainframe, distributed and cloud environments. Synchronisation creates a more consistent foundation for operations, analytics and AI.
One connected flow
Capture once. Transform with control. Deliver wherever the business needs data.
RDRS combines real-time CDC, integrated transformation and one-to-many distribution without multiplying custom integration pipelines.
Capture
Read committed inserts, updates and deletes from source transaction logs without adding query load to production databases.
Transform
Map, translate and convert mainframe data formats for distributed, cloud, analytics and streaming platforms.
Distribute
Capture once and apply changes to multiple targets, including bidirectional flows where connected systems must remain aligned.
Recover
Use checkpoints, restartable pipelines, rollback controls and integrity checks to resume accurately after interruptions.
Trusted operational data
Put current data to work across the enterprise.
Zero compromise on data integrity
Keep information aligned across mainframe, distributed and cloud environments so modern applications, analytics and AI can work from a trusted operational foundation.
- Preserve transactional consistency
- Apply committed changes in order
- Monitor and validate synchronisation
Power real-time AI and analytics
Stream current operational data to feature stores, event-driven platforms and dashboards so decisions reflect business activity rather than the last batch snapshot.
Accelerate hybrid modernisation
Connect established systems to cloud and event-driven platforms without forcing immediate application rewrites or disruptive migrations.
Maintain resilient replication
Handle outages, maintenance windows and infrastructure changes with restartable pipelines, recovery controls and schema-change handling.
Platform coverage
Bring mainframe, cloud and distributed data into sync.
Representative source and target families supported by RDRS, based on Rocket Software’s published platform coverage.
Supported source families
Supported target families
Plan the data flow
Make current enterprise data available where it creates value.
Talk with CCA about the source systems, target platforms, latency requirements and recovery controls that shape a dependable RDRS implementation.
