Dataverse Elastic tables

Hello Power Enthusiats and Technology Evangelists, here is my another blog. This blog focuses on the details that developers need to know while using elastic tables.

Your Dataverse database capacity utilization includes elastic tables, just like regular tables do.

What is an Elastic Table?

Unlike normal Dataverse tables, which are driven by Azure SQL Database, Elastic tables are powered by Azure Cosmos Database, which is built to manage massive amounts of data and high levels of throughput with low latency.

Elastic tables are ideal for applications with unpredictable, spiky, or rapidly increasing workloads. Like standard tables, elastic tables have the same well-known user interface and API.

They have many of the same features and settings as standard tables, but they also have special features and capabilities that are made possible by Azure Cosmos DB.

Here are some circumstances where elastic tables can be used.

• Your data may be unstructured or semi-structured, and your data model
  may be continually changing.


• You require automated horizontal scaling.


• You must manage a high volume of read and write requests.

How to create Elastic tables?

To build an elastic table, simply follow the standard steps given below:

• In Power platform select Tables > + New table dropdown > Table(advanced properties.

Currently, the elastic tables do not support several common Dataverse table features:

Individuals who are unfamiliar with Azure Cosmos DB may struggle to figure out how it works. Let us go into more depth, and I will do my best to provide a comprehensive explanation.

Partitioning and horizontal scaling

Azure Cosmos DB partitions individual containers in a database to satisfy the performance requirements of your application. The items in a container are separated into discrete subsets known as logical partitions. Logical partitions are created based on the value of a partition key associated with each item in a container. All of the elements in a logical partition share the same partition key value.

For example, an Azure Cosmos DB container holds items and each item has a unique value for the CountryName property. If CountryName serves as the partition key for the items in the container and there are 10 unique CountryName values, 10 logical partitions are created for the container.

Additionally each item in a container has an item ID, which is unique within a logical partition. Combining the partition key and the item ID yields the item's index, which uniquely identifies the item. Choosing a partition key is a critical decision that affects your application's performance.