Q5 — AWS SAA-C03 Ch.17

Question 5 of 89 | ← Chapter 17

Q1305. A company wants to run a production database in the AWS Cloud. The database will collect billions of sensor readings from multiple locations across multiple AWS Regions. Data is written to the database at a sustained rate of 50,000 writes per second.The company will run reports once every 3 months against the database. The company will run simple queries to retrieve data based on unique location IDs to run the reports. The query results will vary in size. The company needs a solution that will optimize data storage costs. The solution must be highly durable and must not compromise database performanceWhich solution will meet these requirements?

Correct Answer: B. Use Amazon DynamoDB Standard tables, and enable DynamoDB Accelerator(DAX).

Explanation

Let's analyze each option based on the requirements of handling a high - write rate (50,000 writes per second), optimizing data storage costs, ensuring high durability, and not compromising database performance for a production database collecting sensor readings from multiple regions:Option A: Use Amazon Aurora Serverless v2 in one Region. Specify the desired capacity range Write performance: Amazon Aurora Serverless v2 can scale its compute and memory resources automatically to handle varying workloads. However, for a sustained write rate of 50,000 writes per second, relying on a single - region deployment might face limitations in terms of scalability and availability. A single- region solution is also more vulnerable to regional outages, which could disrupt the database service. Storage cost: While Aurora Serverless v2 can be cost - effective for variable workloads, it may not be the most optimized for storing large amounts of data over time, especially when considering the long - term storage of billions of sensor readings.Durability: Aurora provides high durability within a single region, but a multi - region approach would offer even better disaster recovery capabilities. So, this option may not fully meet the requirements. Option B: Use Amazon DynamoDB Standard tables, and enable DynamoDB Accelerator (DAX) Write performance: Amazon DynamoDB is a fully managed NoSQL database service that is designed to handle high - throughput workloads. It can easily handle a sustained write rate of 50,000 writes per second and can scale horizontally to accommodate even higher write volumes. Storage cost: DynamoDB Standard tables offer a cost - effective way to store large amounts of data. The pay - per - request pricing model allows you to only pay for the read and write capacity you use, and for long- term storage of large datasets, it can be more cost - efficient compared to some other database options. Durability: DynamoDB provides high durability by replicating data across multiple Availability Zones within a region. Additionally, you can use global tables to replicate data across multiple regions, further enhancing durability and availability.Performance for reports: Enabling DynamoDB Accelerator (DAX) can significantly improve the performance of read - intensive workloads. For the quarterly reports that involve simple queries based on unique location IDs, DAX can cache the frequently accessed data in memory, reducing the latency of query responses and not compromising the overall database performance. This option meets all the requirements. Option C: Deploy an Amazon RDS for PostgreSQL DB instance, and create a read replica Write performance: Amazon RDS for PostgreSQL is a relational database service. While it can handle a significant amount of write traffic, achieving a sustained write rate of 50,000 writes per second may require a complex and expensive setup with multiple instances and proper sharding. It is not as inherently scalable for high - write workloads as DynamoDB.Storage cost: RDS for PostgreSQL may not be as cost - effective for storing billions of sensor readings over time compared to DynamoDB, especially when considering the storage and compute resources required to handle the high write rate.Durability: RDS provides high durability within a single region, but similar to Aurora, a multi - region approach would be needed for better disaster recovery, which adds complexity and cost. So, this option is not the best fit.Option D: Use Amazon DynamoDB Standard - IA tables in multiple Regions. Configure DynamoDB to manage capacityWrite performance: DynamoDB Standard - IA (Infrequent Access) tables are designed for data that is accessed less frequently. They have higher read and write latency compared to Standard tables, which may not be suitable for a sustained write rate of 50,000 writes per second where low - latency writes are crucial. Storage cost: Although Standard - IA tables offer lower storage costs for infrequently accessed data, the higher latency and potential performance impact make them an inappropriate choice for a high - write production database. So, this option does not meet the requirements. Therefore, the solution that will meet the requirements is Option B.