SAA-C03 · Question #350
A company has 5 TB of datasets. The datasets consist of 1 million user profiles and 10 million connections. The user profiles have connections as many-to-many relationships. The company needs a…
The correct answer is B. Use Amazon Neptune to store the datasets with edges and vertices. Query the data to find. Amazon Neptune is a fully managed graph database service optimized for storing and navigating complex many-to-many relationships like social graphs or network topologies. It supports Gremlin and openCypher queries that allow efficient traversal of connections even multiple…
Question
A company has 5 TB of datasets. The datasets consist of 1 million user profiles and 10 million connections. The user profiles have connections as many-to-many relationships. The company needs a performance-efficient way to find mutual connections up to five levels. Which solution will meet these requirements?
Options
- AUse an Amazon S3 bucket to store the datasets. Use Amazon Athena to perform SQL JOIN
- BUse Amazon Neptune to store the datasets with edges and vertices. Query the data to find
- CUse an Amazon S3 bucket to store the datasets. Use Amazon QuickSight to visualize
- DUse Amazon RDS to store the datasets with multiple tables. Perform SQL JOIN queries to find
How the community answered
(19 responses)- A11% (2)
- B79% (15)
- C5% (1)
- D5% (1)
Explanation
Amazon Neptune is a fully managed graph database service optimized for storing and navigating complex many-to-many relationships like social graphs or network topologies. It supports Gremlin and openCypher queries that allow efficient traversal of connections even multiple levels deep. SQL JOINs (Athena or RDS) are inefficient for deep relationship queries due to exponential complexity. QuickSight is used for data visualization, not graph traversal.
Community Discussion
No community discussion yet for this question.