Azure SQL DB, Azure Dedicated SQL pool (formerly known as Azure SQL Data Warehouse), and Elastic Pool are three different tools offered in Microsoft Azure for managing and deploying SQL databases.
Here’s a breakdown of each:
Azure SQL DB:

Azure SQL DB or Azure SQL Database is a fully managed, cloud-based relational database service provided by Microsoft Azure. It is designed to host and manage SQL databases in the cloud without requiring the administration of underlying infrastructure.
Azure SQL DB offers a range of deployment options, including single databases and managed instances.
It provides features such as automatic backups, automated patching, built-in high availability, and scalability.
Azure Dedicated SQL pool:

Azure Dedicated SQL pool (formerly Azure SQL Data Warehouse) is a distributed, columnar data storage and analytics service in Azure. It is designed to handle large volumes of data and support complex analytical queries.
Azure Dedicated SQL pool uses massively parallel processing (MPP) architecture to scale compute and storage resources independently, allowing for high-performance analytics on large datasets.
It is suitable for data warehousing, business intelligence, and analytics workloads.
Elastic Pool:

Azure SQL Elastic Pool is a resource allocation model that allows you to manage and share resources among multiple Azure SQL databases. It provides a cost-effective solution for consolidating databases with varying and unpredictable workloads.
With Elastic Pool, you define the resources (e.g., compute and storage) that are shared among a group of databases. The pool dynamically adjusts resources based on the needs of each database within the pool, allowing for efficient resource utilization and cost savings.
In simpler terms, Azure SQL DB is a fully managed relational database service, Azure Dedicated SQL pool is a distributed analytics service for large datasets, and Elastic Pool is a resource allocation model for managing multiple SQL databases with varying workloads.
Each of them are designed to address different use cases and requirements in the Azure ecosystem.
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