Expensive
Keeping years of inactive data in production systems increases infrastructure, database, backup, licensing, and maintenance costs.
Datacyclic helps enterprises move historical data out of expensive applications and databases while keeping it accessible, governed, auditable, and ready when business, legal, or regulatory teams need it.
Keeping years of inactive data in production systems increases infrastructure, database, backup, licensing, and maintenance costs.
Deleting historical data without the right controls can create audit, legal, compliance, and business risk.
Retiring an application becomes difficult when historical information must remain available long after daily operations stop.
When a legacy application is no longer needed for daily operations, enterprises often continue paying for licenses, infrastructure, support, databases, and security simply because the historical data cannot disappear.
Datacyclic separates the data from the application.
Historical data remains trapped inside infrastructure designed for active business operations.
Move historical information into a governed archive designed for long-term preservation and access.
Move inactive history out of expensive production systems.
Reduce dependency on software and infrastructure needed only for historical access.
Keep information available without keeping the original application running.
Maintain the controls needed to manage historical data after the application is gone.
From the moment data leaves production until its retention obligation ends.
Connect to enterprise databases and supported storage systems while capturing the metadata required to understand archived information.
Identify historical information and define archive, retention, and lifecycle rules around the data being preserved.
Extract historical data and store it in efficient archive formats such as Parquet in customer-controlled storage.
Maintain metadata, lineage, retention policies, access controls, audit history, and lifecycle information around archived data.
Datacyclic orchestrates the journey from production data to long-term archive and eventual policy-driven disposal.
Connect to enterprise databases and supported storage systems while capturing the metadata required to understand archived information.
Choose tables, records, business objects, or historical data that should move out of production.
Configure archive rules, retention requirements, and lifecycle policies for the data being preserved.
Extract historical data and store it in efficient, portable archive formats such as Parquet.
Register metadata, schema information, lineage, archive location, and other information required to understand the archive.
Browse archived datasets and make historical information available when authorized users need it.
Manage retention policies, access controls, audit history, and preservation requirements throughout the lifecycle.
Purge data when its retention obligation has ended and policy allows disposal.
Historical data can remain available without keeping the original production application running.
Archiving is not complete when data leaves production. Historical information still needs context, controls, traceability, and a lifecycle that can be understood later.
Datacyclic Governance layer Datacyclic gives enterprises the flexibility to deploy where their data needs to live — without forcing critical archive data into a SaaS-only platform.
Deploy Datacyclic inside your organization's cloud environment and archive data directly into storage you own and manage.
Run Datacyclic within your own data center, private cloud, or enterprise infrastructure while keeping archive operations internal.
Connect cloud and on-premise environments while managing the entire archive lifecycle through one governed Datacyclic platform.
Datacyclic is built to help teams manage the operational side of data archiving and lifecycle management from a single control plane.
Explore the documentation →Integrate with enterprise identity systems and manage role-based access to platform capabilities and archived data.
Run archival workloads designed to move historical data out of expensive production environments.
Define lifecycle policies that govern how long archived information must be retained.
Maintain traceability around archive activity, policy actions, and lifecycle operations.
Use efficient archive formats and customer-controlled storage designed for long-term accessibility.
Move historical data out of expensive production systems while keeping it accessible, governed, and ready when you need it.