No. DataFrugal is a cloud backup and data control platform, not a file collaboration or personal storage service.

• Purpose-built for backup, retention, and recovery workflows
• No file sync or real-time collaboration features
• Designed for enterprise governance, not end-user storage

DataFrugal manages and operates secure object storage as part of its platform, optimized specifically for backup and data protection.

• Storage is encrypted and policy-governed
• Access is controlled through platform workflows
• Not exposed for general-purpose file access or sharing

Customers retain logical ownership and operational control over their data. DataFrugal enforces access, retention, and encryption policies at the platform level.

• Role-based and organization-scoped access
• Policy-driven retention and recovery
• No inspection or analysis of data content

No. DataFrugal is designed to operate alongside existing applications and cloud infrastructure.

• Complements application and system storage
• Provides backup, retention, and recovery capabilities
• Does not replace collaboration or productivity tools

No. DataFrugal does not inspect, analyze, or process file contents.

• Operations are based on metadata only
• Content remains private and untouched
• This minimizes security exposure and compliance risk

DataFrugal enables recovery by providing controlled access to retained versions of protected data.

• Download specific versions using the UI, APIs, or df-agent
• Restore data using your own application or system processes
• No automated reintegration or in-place recovery workflows
• No inspection or modification of data content by DataFrugal

DataFrugal pricing is usage-based and aligned to the volume of data protected, not the number of users.

• No per-user or per-seat licensing
• Predictable costs as teams and automation scale
• Aligned with infrastructure usage, not headcount

df-agent is a lightweight command-line agent used for system-level and automated data operations.

• Runs on Unix-based systems
• Enables CLI-driven and scripted workflows
• Commonly used in CI/CD pipelines and scheduled jobs
• Does not expose underlying storage credentials

No. df-agent is optional and intended for automation-heavy or system-integrated workflows.

• Teams can operate entirely through the web UI if needed
• APIs and df-agent are used when automation or scale is required
• Both approaches operate under the same security and policy controls

No. DataFrugal does not expose S3 endpoints or cloud storage SDKs directly.

• All interactions occur through DataFrugal APIs or df-agent
• Underlying storage complexity is abstracted by the platform
• This reduces credential sprawl and misconfiguration risk

DataFrugal operates as a control and orchestration layer between your applications and underlying cloud storage.

• Receives data from applications, systems, or automation
• Applies retention, versioning, and access policies
• Manages secure storage and recovery workflows

No. DataFrugal is designed to integrate without requiring application rewrites.

• Can be introduced alongside existing systems
• Supports incremental adoption
• Does not interfere with application runtime behavior

DataFrugal enforces preventive access controls at the platform level to reduce the risk of unauthorized access.

• Role-based access control (RBAC) to scope permissions
• IP allow-listing to restrict access to approved networks
• Organization-scoped access with no public sharing model

These controls are enforced by design, minimizing reliance on reactive alerts or manual enforcement.

DataFrugal supports multiple underlying storage backends, including AWS and Wasabi. The choice depends on workload characteristics and retention needs.

• AWS-backed storage is suited for workloads with frequent access, flexible lifecycle requirements, and region availability.
• Wasabi-backed storage is suited for long-term retention and archival use cases with predictable access patterns and no egress charges.

Once a backend is selected for a dataset, it is typically fixed to ensure consistency and predictable operations. DataFrugal abstracts backend differences through its platform APIs and controls.

DataFrugal pricing is based on actual usage and is aligned to the amount of data protected rather than the number of users.

• Platform subscription – a fixed monthly base charge
• Storage usage – calculated in predefined storage units (slabs)
• Data egress – applicable only for certain backends such as AWS

Usage is measured monthly, and costs scale predictably as data grows. API usage is currently included as part of the subscription under fair use limits.

Detailed examples and backend-specific rates are available on the pricing page.

Detailed pricing depends on factors such as data volume, selected storage backend, and usage patterns.

To ensure accurate and transparent pricing, detailed rate cards and backend-specific charges are shared directly with customers. Please Contact Us to receive pricing details tailored to your requirements.