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Question 337 - SAA-C03 discussion

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A company wants to migrate an Oracle database to AWS. The database consists of a single table that contains millions of geographic information systems (GIS) images that are high resolution and are identified by a geographic code. When a natural disaster occurs tens of thousands of images get updated every few minutes. Each geographic code has a single image or row that is associated with it. The company wants a solution that is highly available and scalable during such events Which solution meets these requirements MOST cost-effectively?

A.
Store the images and geographic codes in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance
Answers
A.
Store the images and geographic codes in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance
B.
Store the images in Amazon S3 buckets Use Amazon DynamoDB with the geographic code as the key and the image S3 URL as the value
Answers
B.
Store the images in Amazon S3 buckets Use Amazon DynamoDB with the geographic code as the key and the image S3 URL as the value
C.
Store the images and geographic codes in an Amazon DynamoDB table Configure DynamoDB Accelerator (DAX) during times of high load
Answers
C.
Store the images and geographic codes in an Amazon DynamoDB table Configure DynamoDB Accelerator (DAX) during times of high load
D.
Store the images in Amazon S3 buckets Store geographic codes and image S3 URLs in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance.
Answers
D.
Store the images in Amazon S3 buckets Store geographic codes and image S3 URLs in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance.
Suggested answer: B

Explanation:

Amazon S3 is a highly scalable, durable, and cost-effective object storage service that can store millions of images1. Amazon DynamoDB is a fully managed NoSQL database that can handle high throughput and low latency for key-value and document data2. By using S3 to store the images and DynamoDB to store the geographic codes and image S3 URLs, the solution can achieve high availability and scalability during natural disasters. It can also leverage DynamoDB's features such as caching, auto-scaling, and global tables to improve performance and reduce costs2. a) Store the images and geographic codes in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance. This solution will not meet the requirement of scalability and cost-effectiveness, as Oracle is a relational database that may not handle large volumes of unstructured data such as images efficiently3. It also involves higher licensing and operational costs than S3 and DynamoDB12.

c) Store the images and geographic codes in an Amazon DynamoDB table Configure DynamoDB Accelerator (DAX) during times of high load. This solution will not meet the requirement of cost- effectiveness, as storing images in DynamoDB will consume more storage space and incur higher charges than storing them in S312. It will also require additional configuration and management of DAX clusters to handle high load. d) Store the images in Amazon S3 buckets Store geographic codes and image S3 URLs in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance. This solution will not meet the requirement of scalability and cost-effectiveness, as Oracle is a relational database that may not handle high throughput and low latency for key-value data such as geographic codes efficiently3. It also involves higher licensing and operational costs than DynamoDB2. Reference URL: https://dynobase.dev/dynamodb-vs-s3/


asked 16/09/2024
Jeremy Cheeseborough
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