Menu Close

Tag: What is the difference between Standard and Elastic tables in Dataverse?

What is the difference between Standard and Elastic tables in Dataverse?

Hello Everyone,

Today I am going share my thoughts on the Elastic vs Standard Table in Dynamics 365.

Let’s get’s started.

Certainly! In Dynamics 365, let’s explore the difference between Elastic tables and Standard tables in Dataverse.

1. Standard Tables:

Included with Power Platform: Standard tables, also known as out of box tables, come pre-defined within a Power Platform environment that includes Microsoft Dataverse.

Examples: Some common standard tables include Account, Business Unit, Contact and User tables.

Customization: Most standard tables can be customized to suit your specific needs.

Managed Solution Import: Tables imported as part of a managed solution and set as customizable also appear as standard tables.

Activity Tables: These are a special type of standard table, best suited for rows related to activities(e.g appointment, tasks, emails).

Ownership: Standard tables can be owned by users or teams.

2. Elastic Tables:

Managed by Dataverse: Elastic tables are managed by Microsoft Dataverse.

Azure Cosmos DB: They share the same user experience and API as standard tables but have unique features powered by Azure Cosmos DB.

Large Datasets: Elastic tables are designed for storing very large datasets, often exceeding tens of millions of rows.

Behind the scenes: While standard tables are stored in an Azure SQL database, elastic tables use Cosmos DB.

Benefits: Elastic tables offer benefits like scalability, flexibility, and global distribution.

Limitation: However, they come with some limitations due to their underlying technology.

In summary, choose standard tables for strong data consistency, relational modeling and complex joins. Elastic tables are ideal for handling massive datasets while leveraging the power of Azure Cosmos DB.

That’s it for today.

I hope this helps.

Malla Reddy Gurram(@UK365GUY)
#365BlogPostsin365Days

Share this: