Database to database
Move eligible historical data from a production database into a dedicated archive database while keeping the live application focused on active data.
Move historical data out of expensive production systems, preserve it in a governed archive, keep it accessible when required and manage everything from retention and legal hold to restore and purge.
Datacyclic is designed to manage what happens after data leaves the production application—not just the extraction process.
Keep recent and active data in production while moving eligible historical information into a dedicated, governed archive.
Move eligible historical data from a production database into a dedicated archive database while keeping the live application focused on active data.
Extract historical data, store it efficiently as Parquet and retain it in customer-controlled object storage for long-term preservation.
Users can browse available archives, inspect stored information and understand what is available before deciding whether a restore is required.
Explore available archived tables and datasets from a centralized archive catalog.
Understand when and how information was archived and where it is stored.
View the structure of archived information to help make sense of the data later.
Retrieve approved archived information for downstream use or review.
Avoid unnecessary bulk recovery. Browse the archive and restore individual records, selected data, date ranges or complete datasets.
Bring back only the records required instead of restoring an entire archive.
Restore historical information for a selected period.
Restore a full archived table or dataset when required.
Restore the complete archived dataset for broader recovery needs.
Control how long information is preserved, protect it with legal hold when necessary and apply policy-driven purge at the appropriate time.
Define how long archived information must be preserved.
Protect data from purge while legal or regulatory requirements remain active.
Identify information that has reached the end of its retention period.
Remove eligible data according to configured policies and controls.
Integrate enterprise authentication and control exactly what each user or group can access across the Datacyclic platform.
Integrate with enterprise identity providers for centralized, controlled authentication.
Define permissions based on user responsibilities and control access to administration, operations and archived data.
Manage the overall platform, users, roles and enterprise configuration.
Manage connections, archive jobs, policies and operational configuration.
Configure and support archive workloads within assigned permissions.
Browse and access approved archived information without administrative access.
Give management teams visibility into archive growth, execution speed, operational trends, failures and overall archive health.
Track archive volume, execution speed, performance trends, job health and failures from one operational view.
The archive process could not complete successfully.
Connection, extraction or source-system resource availability may require review.
Review the job details, validate the source connection and retry after resolving the issue.
Maintain an auditable history of important archive activity so teams can review operational actions and lifecycle events when required.
Track archive execution and relevant job activity.
Review important lifecycle protection actions.
Maintain visibility into archived information brought back for use.
Record lifecycle actions taken when data becomes eligible for removal.
When a legacy application becomes expensive to license, maintain and support, preserve the historical data separately and reduce dependency on the original application.
Datacyclic is designed around customer-controlled deployment and storage rather than a SaaS-only operating model.
Deploy within a customer-controlled cloud environment using customer-managed infrastructure and storage.
Deploy inside enterprise infrastructure, private cloud or customer-managed data centres.
Operate across cloud and on-premise environments based on enterprise requirements.
Archive historical information, keep it accessible, manage retention and legal hold, restore when required and reduce dependency on expensive production and legacy systems.