SAA-C03 DAX is an in-memory cache for DynamoDB. Practice Question
A read-heavy document portal repeatedly queries the same product catalogue data from DynamoDB with millisecond latency requirements. Which service can reduce read latency and table load? The design must avoid adding custom operational scripts.
⚠ Common exam trap
Many exam-takers confuse caching services like ElastiCache with DAX, but DAX is purpose-built for DynamoDB and requires no application code changes beyond pointing to a different endpoint, whereas ElastiCache would need custom cache invalidation logic.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
DynamoDB Accelerator (DAX)
DynamoDB Accelerator (DAX) is an in-memory cache for DynamoDB that delivers microsecond read latency, reducing the number of read requests hitting the underlying table. It requires no custom scripts—just a DAX cluster endpoint—and automatically caches frequently accessed items, making it ideal for a read-heavy document portal with millisecond latency requirements.
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 Kinesis Data Firehose
Why it's wrong here
Amazon Kinesis Data Firehose is a fully managed streaming ingestion service that reliably buffers and loads near-real-time data into destinations like Amazon S3, Redshift, or OpenSearch. It cannot serve as an in-memory cache for DynamoDB read operations, nor does it intercept GetItem or Query calls. Because the document portal repeats the same product lookup, the missing component is a low-latency read cache, not a streaming data pipeline.
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S3 Transfer Acceleration
Why it's wrong here
S3 Transfer Acceleration uses AWS edge locations to speed up uploads and downloads to and from Amazon S3 over long distances by routing traffic along optimized network paths. It has no relationship to DynamoDB request latency and does not cache the results of product queries; a client still hits DynamoDB for every read. The bottleneck in a read-heavy document application is repeated database point reads, which requires a caching layer that can serve those items without invoking DynamoDB each time.
- ✓
DynamoDB Accelerator (DAX)
Why this is correct
DynamoDB Accelerator (DAX) is a fully managed, highly available in-memory cache that sits in front of DynamoDB and transparently intercepts GetItem, BatchGetItem, and Query calls, returning cached items in microseconds. It uses a write-through strategy that keeps the cache coherent with the underlying table, making it ideal for read-heavy workloads that repeatedly query the same items, like this document portal. DAX also reduces read capacity unit consumption and protects the table from unexpected throttling on hot keys.
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AWS Glue Data Catalog
Why it's wrong here
AWS Glue Data Catalog is a persistent metadata store that contains table schemas, partitions, locations, and other data descriptors for analytics engines such as Athena, EMR, and Redshift Spectrum. It does not cache application data or intercept DynamoDB queries, so it cannot reduce read latency for the document portal. Using Glue Catalog would be relevant for data discovery and ETL processing, not for accelerating repeated point reads on a live application.
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