1 Choosing an AWS Database Free Online FlashCards

What should guide an AWS database choice?

Start with the data shape, read and write patterns, consistency needs, expected scale, availability targets, and cost constraints—not a favorite service.

When is a relational database a good fit?

Use a relational database when the application needs related data, SQL joins, constraints, transactions across records, or flexible queries not all known in advance.

What is Amazon RDS suited to?

Amazon RDS is a managed service for familiar relational engines, including PostgreSQL, MySQL, MariaDB, SQL Server, Oracle, and Db2.

When should you consider Amazon Aurora?

Consider Aurora when PostgreSQL or MySQL compatibility fits and the workload benefits from Aurora’s cluster architecture, scaling, or availability features.

What should guide DynamoDB key design?

Design DynamoDB tables and keys around the queries the application must perform; key-centered access suits predictable lookups and updates.

How can DynamoDB items vary in structure?

DynamoDB items are identified by primary keys and can contain attributes whose structure varies between items.

What read consistency does DynamoDB commonly provide by default?

DynamoDB provides eventually consistent reads by default in many cases, and strongly consistent reads for supported table and local-secondary-index reads.

Which DynamoDB features do not support strongly consistent reads?

Global secondary indexes and streams do not support strongly consistent reads.

What do DynamoDB transactions provide?

DynamoDB transactions support coordinated, all-or-nothing changes across items, but can add work and cost.

When might Amazon DocumentDB fit better than DynamoDB?

Consider a document-oriented database such as Amazon DocumentDB when queries need to search across JSON-like document fields.

What workload is Amazon Redshift designed for?

Amazon Redshift is a data warehouse for OLAP workloads such as reporting, aggregation, and queries over large datasets.

How does Redshift support analytical queries?

Redshift uses columnar storage and massively parallel processing to scan and analyze data efficiently.