Pricing
Pricing shaped around how you deliver analytics
Datafor is packaged for three scenarios: internal BI, enterprise-scale rollout, and embedded analytics for commercial products.
Three editions, three clear use cases
Standard
For organizations using Datafor as an internal BI platform.-
Self-hosted BI and dashboards
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Semantic modeling and reusable metrics
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ACL, RLS, and OLS governance
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SSO and enterprise authentication
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Creator and Reader user model
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Core governed analytics for teams that need dashboards, reporting, semantic models, and controlled self-service.
Enterprise
For larger internal deployments with deeper integration needs.-
Everything in Standard
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Advanced deployment architecture
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Deeper API and integration support
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More extensibility for enterprise environments
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Expanded service and SLA options
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Adds the deployment flexibility, integration support, and operational packaging needed for broader enterprise use.
Popular
OEM
For software vendors embedding analytics into their own product.-
Everything in Enterprise Edition
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White-label branding
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Embedded delivery and integration support
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Multi-tenancy and tenant packaging
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OEM licensing and support model
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Built for customer-facing delivery, including white-label branding, tenant packaging, and OEM-style commercial terms.
Where the editions should differ
| Capability | Standard | Enterprise | OEM |
|---|---|---|---|
| Self-service BI and dashboards | Yes | Yes | Yes |
| Semantic modeling and governed metrics | Yes | Yes | Yes |
| ACL, RLS, OLS, and enterprise auth | Yes | Yes | Yes |
| Internal analytics deployment | Yes | Yes | Yes |
| Advanced integration and extensibility | Basic | Yes | Yes |
| Embedded analytics delivery | No | Yes | Yes |
| White-label branding | No | No | Yes |
| Multi-tenant customer packaging | No | No | Yes |
| Commercial redistribution / OEM terms | No | No | Yes |
Common questions
Start with the delivery model. Choose Standard for internal BI, Enterprise Edition for broader enterprise rollout and integration, and OEM when analytics is part of the software product you deliver to your own customers.
Not always. Enterprise Edition can fit some embedded enterprise scenarios, but OEM is usually the right choice when the analytics experience is customer-facing and commercially packaged.
OEM is designed for product delivery. It brings together white-label branding, multi-tenant packaging, and commercial terms built for software vendors and embedded analytics use cases.
No. AI is better packaged as an extension across editions. It can be enabled separately, connected to external LLM providers, and permission-controlled based on your deployment needs.
Yes. Governance is foundational across Datafor, including access control, semantic modeling, and enterprise authentication. The main differences between editions are delivery model, extensibility, and commercial packaging.
No. Datafor is designed for self-hosted deployment so organizations can control infrastructure, security, and data residency.
