SAA-C03 · Question #703
A company wants to migrate terabytes of frequently used JSON documents to AWS. The solution must allow fast JSON document queries that combine data from multiple sources, perform calculations on…
The correct answer is C. Store the documents in Amazon DocumentDB (with MongoDB compatibility). Run queries on the. Amazon DocumentDB is designed for storing and querying large volumes of JSON documents with flexible schemas, making it well suited for evolving document structures. It supports rich, fast queries across documents, including combining data, filtering, and pattern matching…
Question
A company wants to migrate terabytes of frequently used JSON documents to AWS. The solution must allow fast JSON document queries that combine data from multiple sources, perform calculations on datasets, and search for text patterns within the data. The company expects the structure of the JSON documents to change in the future. Which solution will meet these requirements?
Options
- AConvert the documents to a relational data structure. Store the documents in an Amazon RDS DB
- BStore the documents in an Amazon S3 bucket. Use Amazon Athena to perform SQL queries on
- CStore the documents in Amazon DocumentDB (with MongoDB compatibility). Run queries on the
- DStore the JSON data in Amazon DynamoDB. Run queries on the stored data.
How the community answered
(54 responses)- A4% (2)
- B11% (6)
- C69% (37)
- D17% (9)
Explanation
Amazon DocumentDB is designed for storing and querying large volumes of JSON documents with flexible schemas, making it well suited for evolving document structures. It supports rich, fast queries across documents, including combining data, filtering, and pattern matching, without requiring schema redesign as the JSON format changes.
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