SOA-C02 Networking and Content Delivery Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

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  Amazon RDS: Relational database

  Why this is correct

  Amazon RDS is a managed relational database service that provides the familiar SQL interface, fixed-schema tables, and ACID transactions across multiple engines such as MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server. It automates administrative tasks like patching, backups, and Multi-AZ failover while still allowing you to connect with standard database clients. RDS is optimized for OLTP workloads, not for key-value access or in-memory caching, which is why its correct category is relational database.

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  Amazon DynamoDB: NoSQL key-value and document database

  Why this is correct

  Amazon DynamoDB is a fully managed NoSQL database that supports both key-value and document data models, delivering predictable single-digit-millisecond latency at any scale. It is serverless and horizontally scalable, automatically partitioning data across multiple Availability Zones to handle high-throughput workloads. Unlike a relational database, DynamoDB does not enforce a fixed schema or support complex SQL joins; access is primarily by partition key and optional sort key, with DynamoDB Accelerator (DAX) available for even lower latency.

• ✓

  Amazon Redshift: Data warehouse

  Why this is correct

  Amazon Redshift is a fully managed, petabyte-scale data warehouse service built on columnar storage and massive parallel processing (MPP). It is designed for OLAP and analytic queries over large historical datasets, using standard SQL to aggregate and join data from multiple sources. Redshift separates compute and storage, lets you pause or resize clusters, and integrates with Amazon S3, Athena, and Glue; it is not an in-memory cache or a row-based OLTP database.

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  Amazon ElastiCache: In-memory cache

  Why this is correct

  Amazon ElastiCache is a managed in-memory caching service that supports two open-source engines, Redis and Memcached, to power sub-millisecond read operations and reduce pressure on backend databases. It removes the operational burden of deploying and patching cache nodes, while offering features such as replication, automatic failover, and online resizing. The service is used to cache frequently accessed data, store sessions, and enable real-time workloads; it is not designed for durable, queryable database storage.

• ✗

  Amazon RDS: NoSQL key-value and document database

  Why it's wrong here

  RDS is not a NoSQL database. RDS is a relational database management service, meaning it uses structured schemas, SQL, and ACID transactions; categorizing it as a NoSQL key-value store would be factually incorrect. If your workload requires key-value or document data models with flexible schemas and horizontal scaling, Amazon DynamoDB is the AWS service designed for that purpose. RDS supports only SQL-based engines and is a poor fit for the access patterns that motivate choosing a NoSQL store like DynamoDB.

• ✗

  Amazon Redshift: In-memory cache

  Why it's wrong here

  Redshift is not an in-memory cache. While it can query data very quickly, it is a petabyte-scale data warehouse that persists data on disk in columnar format and uses massive parallel processing to run complex analytical queries. Sub-millisecond, latency-sensitive caching for web applications is the domain of Amazon ElastiCache, which supports Redis and Memcached in memory. Placing Redshift in the in-memory cache category confuses an OLAP warehouse with a pure cache engine; the two services serve fundamentally different tiers of the architecture.

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