Discover the best AWS service for migrating Microsoft SQL Server from on-premises to the cloud. Learn why Amazon RDS is the ideal choice for reducing management overhead while ensuring seamless database operations.
Table of Contents
Question
To migrate Microsoft SQL Server from on-premises to the AWS cloud with reduced management overhead, which AWS service should be used?
A. Amazon Elastic Container Service
B. Amazon SageMaker
C. Amazon RDS
D. Amazon Athena
Answer
C. Amazon RDS
Explanation
Amazon RDS supports multiple database engines, including Microsoft SQL Server, reducing management overhead.
Why Amazon RDS?
Amazon Relational Database Service (Amazon RDS) is a fully managed database service provided by AWS, designed to simplify the deployment and management of relational databases, including Microsoft SQL Server. Here’s why it is the best choice for this scenario:
- Reduced Management Overhead: Amazon RDS automates time-consuming administrative tasks such as database setup, patching, backups, and scaling. This significantly reduces the operational burden compared to self-managing databases on Amazon EC2 or on-premises.
- Compatibility with Microsoft SQL Server: Amazon RDS supports multiple editions of Microsoft SQL Server (e.g., Standard, Enterprise) and provides features like high availability through Multi-AZ deployments and automated backups.
- Scalability and Performance: With Amazon RDS, you can easily scale compute and storage resources based on demand. It also supports performance monitoring and tuning, ensuring optimal database operations.
- Migration Support: AWS provides tools like AWS Database Migration Service (AWS DMS) to facilitate seamless migration from on-premises SQL Server environments to Amazon RDS with minimal downtime.
Amazon RDS is the optimal choice for migrating Microsoft SQL Server to AWS when reducing management overhead is a priority. It offers a fully managed environment tailored for relational databases, ensuring reliability, scalability, and ease of use throughout the migration process.
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