Discover which Amazon database service is best suited for data sets with variations in attributes. Learn how to select between DynamoDB, QLDB, Neptune, and RDS.
Table of Contents
Question
An AWS solutions architect needs a database for a data set that has variations in the data. Not every piece of data shares the same attributes. Which database should the solutions architect choose?
A. Amazon Quantum Ledger Database (Amazon QLDB)
B. Amazon DynamoDB
C. Amazon Neptune
D. Amazon RDS
Answer
B. Amazon DynamoDB
Explanation
Amazon DynamoDB is a nonrelational database that allows for a flexible schema, so each item can have variations in the attributes outside of the primary and secondary key.
Amazon DynamoDB is the most suitable database choice for a data set that has variations in the data where not every item shares the same attributes. This is because DynamoDB is a NoSQL database that provides a flexible schema.
In a DynamoDB table, each item (row) can have a different number and set of attributes (columns). This allows you to store data with varying structures in the same table without having to define a fixed schema upfront. DynamoDB’s flexibility makes it ideal for handling semi-structured or unstructured data.
The other options are not as suitable:
- Amazon QLDB is useful for ledger-like applications needing an immutable and cryptographically verifiable transaction log, but doesn’t provide the same schema flexibility as DynamoDB.
- Amazon Neptune is a graph database used for storing highly connected data in nodes and edges, which isn’t the best fit for this use case.
- Amazon RDS provides managed relational databases which require a predefined, consistent schema. While some RDS engines like PostgreSQL support JSON columns for more flexibility, a NoSQL database like DynamoDB is a better choice overall for highly variable data.
So in summary, the schema flexibility offered by the NoSQL DynamoDB database makes it the best choice for a data set where items don’t necessarily share the same attributes. Its ability to accommodate evolving and non-uniform data structures sets it apart from more rigid database options.
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