Q40 — AWS SAA-C03 Ch.11

Question 40 of 100 | ← Chapter 11

Q740. A social media company wants to store its database of user profiles, relationships, and interactions in the AWS Cloud. The company needs an application to monitor any changes in the database. The application needs to analyze the relationships between the data entities and to provide recommendations to users.Which solution will meet these requirements with the LEAST operational overhead?

Correct Answer: B. Use Amazon Neptune to store the information. Use Neptune Streams to process changes in the database.

Explanation

To meet the requirements of storing a database of user profiles, relationships, and interactions in the AWS Cloud, and to monitor changes in the database while analyzing relationships between data entities and providing recommendations to users with the least operational overhead, the solution that would best fit these requirements is:B. Use Amazon Neptune to store the information. Use Neptune Streams to process changes in the database.Option B, using Amazon Neptune to store the information and Neptune Streams to process changes in the database, would meet the requirements with the least operational overhead.Amazon Neptune is a fully managed graph database service that is optimized for storing and querying highly connected data. It is well-suited for scenarios where relationships between data entities need to be analyzed, such as in social media applications.By using Amazon Neptune to store the user profiles, relationships, and interactions, the social media company can leverage the graph database capabilities to efficiently query and traverse the data, enabling the analysis of relationships and the provision of recommendations to users.Neptune Streams is a feature of Amazon Neptune that allows you to capture changes made to the database and process them in real-time. By using Neptune Streams, the application can monitor any changes in the database and react accordingly. This enables the application to stay up-to-date with the latest changes and provide timely recommendations to users.Option A, using Amazon Neptune to store the information and Amazon Kinesis Data Streams to process changes in the database, is not the most suitable solution for this requirement. While Amazon Kinesis Data Streams can be used to process changes in the database, it introduces additional complexity and operational overhead compared to using Neptune Streams, which is specifically designed for capturing and processing changes in Neptune.Option C, using Amazon Quantum Ledger Database (Amazon QLDB) to store the information and Amazon Kinesis Data Streams to process changes in the database, is not the most suitable solution for this requirement. Amazon QLDB is a fully managed ledger database that provides an immutable and transparent transaction log. However, it may not be the most optimal choice for storing and querying highly connected data with complex relationships, as required by a social media company. Additionally, using Amazon Kinesis Data Streams introduces additional operational overhead compared to using Neptune Streams.Option D, using Amazon Quantum Ledger Database (Amazon QLDB) to store the information and Neptune Streams to process changes in the database, is not the most suitable solution for this requirement. As mentioned earlier, Amazon QLDB may not be the most optimal choice for storing and querying highly connected data with complex relationships. Additionally, Neptune Streams is specifically designed for processing changes in Neptune and would provide a more streamlined and efficient solution compared to using QLDB.Therefore, the most suitable solution that meets the requirements with the least operational overhead is B: Use Amazon Neptune to store the information. Use Neptune Streams to process changes in the database. This solution leverages the graph database capabilities of Amazon Neptune while utilizing Neptune Streams to monitor changes and provide real-time analysis and recommendations.