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Copy file name to clipboardExpand all lines: docs/sql-server/sql-docs-navigation-guide.md
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@@ -4,7 +4,7 @@ description: Tips and tricks for navigating the SQL Server technical documentati
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author: MashaMSFT
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ms.author: mathoma
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ms.reviewer: randolphwest, wiassaf
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ms.date: 03/31/2024
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ms.date: 05/28/2024
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ms.service: sql
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ms.subservice: release-landing
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ms.topic: conceptual
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|**Azure Database for MariaDB**| Fully managed <sup>2</sup> | A relational database service based on the MariaDB open-source database engine. A fully managed database-as-a-service (DBaaS) that can handle mission-critical workloads with predictable performance, security, high availability, and dynamic scalability. |
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|**Azure Database for MySQL**| Fully managed <sup>2</sup> | A relational database service based on the MySQL open-source database engine. A fully managed database-as-a-service (DBaaS) that can handle mission-critical workloads with predictable performance, security, high availability, and dynamic scalability. |
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|**Azure Database for PostgreSQL**| Fully managed <sup>2</sup> | A relational database service based on the PostgreSQL open-source database engine. A fully managed database-as-a-service (DBaaS) that can handle mission-critical workloads with predictable performance, security, high availability, and dynamic scalability. |
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|**Azure Synapse Analytics**| Fully managed <sup>2</sup> |[Azure Synapse Analytics](/azure/synapse-analytics/overview-what-is) is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems. Azure Synapse Analytics brings together the best of SQL technologies used in enterprise data warehousing, Spark technologies used for big data, Data Explorer for log and time series analytics, Pipelines for data integration and ETL/ELT, and deep integration with other Azure services such as Power BI, Cosmos DB, and Azure Machine Learning. The [Azure Synapse SQL](/azure/synapse-analytics/sql/overview-architecture) features provide scale-out architecture for data processing in the form of dedicated SQL pools (formerly SQL DW) and serverless SQL pools. |
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|**Azure Synapse Analytics**| Fully managed <sup>2</sup> |[Azure Synapse Analytics](/azure/synapse-analytics/overview-what-is) is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems. Azure Synapse Analytics brings together the best of SQL technologies used in enterprise data warehousing, Spark technologies used for big data, Data Explorer for log and time series analytics, Pipelines for data integration and ETL/ELT, and deep integration with other Azure services such as Power BI, Cosmos DB, and Azure Machine Learning. The [Azure Synapse SQL](/azure/synapse-analytics/sql/overview-architecture) features provide scale-out architecture for data processing in the form of dedicated SQL pools (formerly SQL DW) and serverless SQL pools. <br /><br />The behavior and Azure portal experience differs between a dedicated SQL pool in Azure Synapse workspaces and a standalone dedicated SQL pool (formerly SQL DW), which lives in a logical SQL server. |
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| **[!INCLUDE [fabric](../includes/fabric.md)]** | Fully managed <sup>4</sup> | [Microsoft Fabric](/fabric/get-started/microsoft-fabric-overview) is an all-in-one, Software-as-a-Service analytics solution for enterprises that covers everything from data movement to data science, real-time analytics, data warehousing, and business intelligence. [[!INCLUDE [fabric](../includes/fabric.md)]](/fabric/data-warehouse/data-warehousing) provides two distinct data warehousing experiences. Each [!INCLUDE [fabric](../includes/fabric.md)] Lakehouse automatically includes a **[!INCLUDE [fabric-se](../includes/fabric-se.md)]** to enable data engineers to access a relational layer on top of physical data in the Lakehouse, thanks to automatic schema discovery. A Synapse Data Warehouse or **[!INCLUDE [fabric-dw](../includes/fabric-dw.md)]** in [!INCLUDE [fabric](../includes/fabric.md)] provides a "traditional" data warehouse and supports the full transactional T-SQL capabilities you would expect from an enterprise data warehouse. Either data warehousing experience exposes data to analysis and reporting tools using T-SQL/TDS end-point. |
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