Introduction
Microsoft offers two low-code data platform options as part of its Power Platform suite - Dataverse and Dataverse for Teams. At a high-level, both enable storing and managing data that can be leveraged across apps, workflows, and analytics. However, there are several key differences under the hood that impact capabilities, integration, licensing and more.
Dataverse provides a relational data environment optimized for building standalone apps and custom line-of-business solutions. It allows enterprise-grade modeling, security, and extensibility powered by a Common Data Service. Dataverse connects extensively with Dynamics 365 and other Microsoft cloud services.
Dataverse for Teams is designed specifically for collaboration, communication, and lightweight workflows in Microsoft Teams. It comes with pre-built data templates for managing lists, tasks, and contacts related to teamwork. The data schema and capabilities are customizable but standardized for Microsoft 365 integrations.
Understanding when to adopt Dataverse versus Dataverse for Teams is an important decision that depends on your use cases, existing stack, and long-term roadmap. In this post, we will do a deep dive into the key technical and business differences between the two platforms. We will explore how data modeling, development, admin experiences, licensing, and integration capabilities differ.
By the end, you will have a clear perspective on when Dataverse or Dataverse for Teams is a better data solution for low-code applications and workflows on the Power Platform.
Let's get started and compare some key areas:
Data Modeling
Dataverse - provides full relational data modeling capabilities to build customized entities, relationships, fields, views and more. This allows flexible data structures optimized for complex business scenarios.
Dataverse for Teams - uses predefined data templates like Contacts, Accounts, Tasks optimized for Microsoft 365 collaboration. The schema is extensible but limited compared to Dataverse's relational custom modeling.
Integrations
Dataverse - A key strength of Dataverse is deep integration with Dynamics 365 and other Microsoft cloud services like Power BI, Power Apps, Power Automate. This unlocks extensive connection capabilities.
Dataverse for Teams - has native integration with Teams, SharePoint, Outlook and other Microsoft 365 workloads. But it has fewer options for external system connectivity.
Development
Dataverse - allows professional developers to build fully custom solutions using plugins, workflow engines, and other extensibility.
Dataverse for Teams - enables business teams to quickly build lightweight collaboration apps using simplified low-code tools like Power Apps and Power Automate.
Admin and Security
Dataverse - provides enterprise-level environment admin controls like managing backups, environments, user permissions and auditing.
Dataverse for Teams - uses inherited Microsoft 365 security groups and policies. This simplifies admin but has less granular control.
Licensing and Access
Dataverse - requires Dynamics 365 or Power Apps premium licensing.
Dataverse for Teams - comes included in certain Microsoft 365 plans.
This means Dataverse may have higher costs but also greater flexibility in allocation. Dataverse for Teams follows Teams licensing rules.
Use Cases
Dataverse - suits structured LOB data and complex modeling needs for custom enterprise solutions.
Dataverse for Teams - fits lightweight data requirements for collaboration use cases inside Microsoft Teams and M365.
Here are some more detailed examples of use cases and applications suited for Dataverse vs Dataverse for Teams:
- Custom CRM or ERP solutions integrated with Dynamics 365.
- LOB applications that require complex data modeling and relationships.
- Applications built on Common Data Service with extensive customization.
- Solutions that leverage Dataverse for process automation and advanced workflow capabilities.
- Applications that connect to many external systems beyond Microsoft 365.
- Power BI analytics and reporting on consolidated, structured enterprise data.
Dataverse for Teams Use Cases
- Lightweight apps and workflows to aid team collaboration.
- Managing contacts, tasks, and plans for a department or project team.
- Simple data collection and reporting needs within a single Team.
- Building chatbots, tabs, and bots to interface with Teams users.
- Automating recurring team workflows like onboarding, status updates etc.
- Quick demos, proofs of concept aligning to Teams users' workflows.
In summary, Dataverse suits heavy custom enterprise application development needs while Dataverse for Teams aligns to lightweight departmental data management and collaboration workflows within Microsoft Teams.
Conclusion
Dataverse and Dataverse for Teams are two data platforms that have some similarities but also some key differences. Dataverse is a more comprehensive platform that allows for relational data modeling with deeper customization, while Dataverse for Teams has predefined schemas optimized for collaboration. Dataverse also connects to the broader Microsoft cloud, including Dynamics 365, while Dataverse for Teams integrates tightly with Microsoft 365 workloads.
In terms of development, Dataverse is focused on professional developers and administrators building custom line-of-business (LOB) apps, while Dataverse for Teams enables low-code collaboration solutions for business teams. When it comes to admin and security, Dataverse provides enterprise-grade admin controls for production, while Dataverse for Teams uses a simplified security model based on Teams roles.
Finally, when it comes to use cases, Dataverse is better suited for structured business data and complex modeling, while Dataverse for Teams fits lightweight data needs supplemented in Microsoft 365.
In conclusion, both platforms have their strengths and weaknesses. It’s important to evaluate both platforms based on your organization’s needs before making a decision.
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