Dataverse virtual tables on SQL: three latency patterns
Dataverse virtual tables allow users to access data from external sources without duplicating it in Dataverse. The performance of these virtual tables is influenced by latency patterns, which are critical for determining their suitability for specific use cases. Three benchmark scenarios are used to evaluate the latency of virtual tables, highlighting the importance of the underlying data source and network conditions.
- ▪Virtual tables in Dataverse enable access to data from SQL Server, Cosmos DB, or REST APIs without data duplication.
- ▪Latency benchmarks are crucial for assessing the performance of virtual tables, with three specific scenarios evaluated.
- ▪The three latency patterns include SQL Server in the same region, REST API calls, and virtual tables with provider-side caching.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3948393) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } SapotaCorp Posted on May 24 • Originally published at sapotacorp.vn Dataverse virtual tables on SQL: three latency patterns #powerplatform Virtual tables let Dataverse surface data that lives in another system - SQL Server, Cosmos DB, a REST API - without copying it into Dataverse. The user-facing experience is the same as any table: views, forms, lookups, relationships. The underlying retrieval goes out over the wire to the external source on every read.
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