Elastic tables are a new type of Dataverse tables physically stored in Azure Cosmos DB, while standard Dataverse tables are stored on Azure SQL. Elastic tables automatically scale horizontally to handle large amounts of data and high levels of throughput with low latency, which makes them suitable for applications with unpredictable, spiky or rapidly growing workloads. When creating a new table object in Dataverse, users can select the new Elastic table type, which comes with some limitations on what can be done.
Elastic tables offer several advantages over standard Dataverse tables. They are able to scale automatically, so users don’t have to worry about scalability or performance issues. They also have low latency, meaning that data is returned quickly, and they can handle unpredictable, spiky or rapidly growing workloads. Additionally, they are much more cost-effective than standard Dataverse tables, as they require fewer resources and less maintenance.
Using Elastic tables is relatively straightforward. After creating a new table object in Dataverse, users can select the new Elastic table type. After this, they can use the standard Dataverse operations to work with their tables, such as creating, retrieving, updating, and deleting data. Users can also use the Azure Portal to monitor their Elastic tables and manage their capacity.
Elastic tables offer several advantages over standard Dataverse tables, including lower latency, scalability, and cost-effectiveness. They are also relatively easy to use, as they can be managed using the standard Dataverse operations. For applications with unpredictable, spiky or rapidly growing workloads, Elastic tables are an ideal solution.