Discover why Amazon Redshift is the best AWS service for migrating on-premises relational data warehouses to the cloud. Learn about its features, scalability, and analytics capabilities for powering dashboards.
Question
A company wants to migrate its on-premises relational data warehouse to AWS. The information in the data warehouse is used to feed analytics dashboards. Which AWS service should the company use for the data warehouse?
A. Amazon ElastiCache
B. Amazon Aurora
C. Amazon RDS
D. Amazon Redshift
Answer
D. Amazon Redshift
Amazon Redshift is the most suitable AWS service for migrating an on-premises relational data warehouse to the cloud, especially when the data is used for analytics dashboards. Here’s why:
Explanation
Amazon Redshift is the AWS data warehousing service, specifically designed for analytics of large volumes of data and ideal for feeding analytics dashboards with large datasets.
Why Amazon Redshift?
Purpose-Built for Data Warehousing
Redshift is a fully managed, cloud-based data warehousing service optimized for online analytical processing (OLAP). It is specifically designed to handle large-scale datasets and complex queries, making it ideal for analytics workloads.
Scalability and Performance
Redshift uses columnar storage and massively parallel processing (MPP) to optimize query performance. It can scale from gigabytes to petabytes of data, ensuring high performance even with growing datasets.
Features like result caching and materialized views further enhance query speeds, making it perfect for powering real-time dashboards.
Integration with Analytics Tools
Redshift integrates seamlessly with popular business intelligence (BI) tools such as Tableau, Power BI, and Amazon QuickSight. This makes it easy to visualize and analyze data directly from the warehouse.
Cost-Effectiveness
Redshift offers a pay-as-you-go pricing model with options for reserved instances, making it more cost-effective compared to traditional on-premises solutions or competitors like Snowflake.
Fully Managed
AWS handles infrastructure management, including provisioning, backups, and scaling, allowing organizations to focus on analytics rather than maintenance.
Why Not the Other Options?
A. Amazon ElastiCache:
ElastiCache is a caching service designed for in-memory data storage and real-time applications like gaming or session management. It is not suitable for data warehousing or analytics workloads.
B. Amazon Aurora:
Aurora is a relational database service optimized for transactional workloads (OLTP), not analytical processing (OLAP). It lacks the scalability and performance features required for large-scale analytics.
C. Amazon RDS:
While RDS supports relational databases, it is primarily intended for transactional workloads. It does not offer the advanced features of Redshift, such as columnar storage or MPP architecture, which are critical for data warehousing.
Amazon Redshift is the best choice for migrating an on-premises relational data warehouse to AWS when the goal is to support analytics dashboards. Its scalability, high performance, seamless integration with BI tools, and cost-effectiveness make it the optimal solution for such use cases.
Amazon AWS Certified Cloud Practitioner CLF-C02 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Amazon AWS Certified Cloud Practitioner CLF-C02 exam and earn Amazon AWS Certified Cloud Practitioner CLF-C02 certification.