AWS Certified Data Analytics Specialty 2021 – Hands-On - DynamoDB Patterns with S3

The video tutorial explains how to efficiently store and manage large objects using Amazon S3 and Dynamic DB. It covers the limitations of Dynamic DB for storing large data and suggests using S3 for such purposes. The process of uploading objects to S3 and storing their metadata in Dynamic DB is detailed, along with strategies for reading and reconstructing data. The tutorial also discusses using Dynamic DB to index S3 metadata, enabling efficient querying and retrieval of data. These strategies leverage the strengths of both services for optimal data management.

Why is DynamoDB not suitable for storing large objects like images and videos?

• It cannot store any type of media files.

• It does not support metadata storage.

• It is too expensive for storing large objects.

• It has a storage limit of 400 kilobytes per item.

What is the role of Amazon S3 in the strategy discussed?

• To replace DynamoDB for all storage needs.

• To store large objects like images and videos.

• To store small metadata objects.

• To provide a backup for DynamoDB data.

How does the application retrieve a large object stored in Amazon S3?

• By querying the S3 bucket directly.

• By using the metadata stored in DynamoDB to get the object's key.

• By scanning the entire S3 bucket.

• By using a predefined URL for each object.

What is one advantage of using DynamoDB to index S3 object metadata?

• It reduces the cost of storing large objects.

• It enables complex queries on object attributes.

• It automatically backs up all S3 data.

• It allows for faster scanning of S3 buckets.

Which AWS service is used to trigger a Lambda function for storing metadata in DynamoDB?

• Amazon S3

• Amazon CloudFront

• Amazon RDS

• Amazon EC2