Support for Synapse SQL serverless in Azure Synapse Link for Azure Cosmos DB

Support for Synapse SQL serverless in Azure Synapse Link for Azure Cosmos DB

Co-authored by Rodrigo Souza, Ramnandan Krishnamurthy, Anitha Adusumilli and Jovan Popovic (Azure Cosmos DB and Azure Synapse Analytics teams) Azure Synapse Link now supports querying Azure Cosmos DB data using Synapse SQL serverless. This capability, available in public preview, allows you to use familiar analytical T-SQL queries and build powerful near real-time BI dashboards on Azure Cosmos DB data.

Co-authored by Rodrigo Souza, Ramnandan Krishnamurthy, Anitha Adusumilli and Jovan Popovic (Azure Cosmos DB and Azure Synapse Analytics teams)

Azure Synapse Link now supports querying Azure Cosmos DB data using Synapse SQL serverless. This capability, available in public preview, allows you to use familiar analytical T-SQL queries and build powerful near real-time BI dashboards on Azure Cosmos DB data.

As announced at Ignite 2020, you can now also query Azure Cosmos DB API for Mongo DB data using Azure Synapse Link, enabling analytics with Synapse Spark and Synapse SQL serverless.

Support for T-SQL queries and building near real-time BI dashboards

Azure Synapse SQL serverless (previously known as SQL on-demand) is a serverless, distributed data processing service offering built-in query execution fault-tolerance and a consumption-based pricing model. It enables you to analyze your data in Cosmos DB analytical store within seconds, without any performance or RU impact on your transactional workloads.

Using OPENROWSET syntax and automatic schema inference, data and business analysts can use familiar T-SQL query language to quickly explore and reason about the contents in Azure Cosmos DB analytical store. You can query this data in place without the need to copy or load the data into a specialized store.

You can also create SQL views to join data in the analytical stores across multiple Azure Cosmos DB containers, to better organize your data in a semantic layer that will accelerate your data exploration and reporting workloads. BI Professionals can quickly create Power BI reports on top of these SQL views in Direct Query mode.

You can further extend this by building a logical data warehouse to create and analyze unified views of data across Azure Cosmos DB, Azure Data Lake Storage and Azure Blob Storage.

 

analytics announcements api for mongodb core (sql) api data architecture query azure cosmos db azure synapse analytics serverless sql pools sql on-demand synapse link synapse sql serverless

What is Geek Coin

What is GeekCash, Geek Token

Best Visual Studio Code Themes of 2021

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Introduction to Structured Query Language SQL pdf

SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.

Analyze Azure Cosmos DB data using Azure Synapse Analytics

This article will help you understand how to analyze Azure Cosmos DB data using Azure Synapse Analytics.

SQL on-demand pools in Azure Synapse Analytics

This article will show how to work with SQL on-demand pools and understand the fundamentals of working with this pool in Azure Synapse Analytics.

How to set up Azure Data Sync between Azure SQL databases and on-premises SQL Server

In this article, you learn how to set up Azure Data Sync services. In addition, you will also learn how to create and set up a data sync group between Azure SQL database and on-premises SQL Server.

Azure SQL | Read Data Lake Files using Synapse SQL External Tables

Azure SQL can read Azure Data Lake storage files using Synapse SQL external tables. Synapse SQL enables you to implement T-SQL functionalities in Azure SQL that read the content of CSV, PARQUET, and JSON files that are placed on Azure Data Lake storage.