Part of the Azure Synapse Analytics suite of services is Synapse Link. This enables synchronization of data from sources including Cosmos DB, SQL Server, Azure SQL Database, and the Dataverse into a Synapse Analytics workspace and makes it available for querying.
Azure Synapse Analytics (formerly SQL Data Warehouse) is a cloud-based data integration and analytics platform from Microsoft. It allows you to bring together structured and unstructured data from a variety of sources, and provides tools for storing, processing, and analyzing that data using SQL and Spark.
Azure Synapse Analytics consists of two main components: a SQL-based data integration and querying engine, and a Spark-based data processing and analytics engine. These components can be used together or independently, depending on your needs.
The SQL-based engine allows you to perform traditional data warehousing tasks, such as loading and transforming data, and running complex queries. The Spark-based engine allows you to perform more advanced analytics tasks, such as machine learning and real-time streaming analytics.
Azure Synapse Analytics is designed to be scalable, flexible, and easy to use. It can be used to support a wide range of data integration and analytics scenarios, including data warehousing, business intelligence, data lakes, and real-time analytics. It is a powerful tool for organizations looking to gain insights from their data and make better informed decisions.
Azure Synapse is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems.
Azure Synapse Analytics is a limitless analytics service that brings together data integration, enterprise data warehousing, and big data analytics. It gives you the freedom to query data on your terms, using either serverless or dedicated options—at scale….
Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or dedicated resources—at scale.
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