DAX (DynamoDB Accelerator) caching - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is DAX in the context of DynamoDB?

DAX stands for DynamoDB Accelerator. It is a caching service that helps speed up read operations by storing frequently accessed data in memory, reducing the time to get data from DynamoDB tables.

beginner

How does DAX improve the performance of DynamoDB?

DAX improves performance by caching read requests in memory. This means repeated reads can be served quickly without going to the DynamoDB database every time, reducing latency from milliseconds to microseconds.

intermediate

What types of DynamoDB operations benefit most from DAX caching?

Read operations like GetItem and Query benefit most from DAX caching because DAX stores the results of these reads in memory for fast retrieval. Write operations are not cached by DAX.

beginner

Does DAX cache write operations to DynamoDB?

No, DAX does not cache write operations. Writes go directly to DynamoDB to ensure data consistency. DAX only caches reads to speed up data retrieval.

intermediate

What happens if data in DynamoDB changes after it has been cached in DAX?

DAX automatically invalidates or updates the cached data when changes happen in DynamoDB to keep the cache consistent. This ensures that clients get fresh data even when using the cache.

What is the main purpose of DAX in DynamoDB?

A To store backups of DynamoDB tables

B To encrypt data stored in DynamoDB

C To speed up read operations by caching data in memory

D To manage user access permissions

DAX is designed to speed up read operations by caching frequently accessed data in memory.

Which DynamoDB operations does DAX cache?

A Read operations only

B Write operations only

C Both read and write operations

D Neither read nor write operations

DAX caches read operations like GetItem and Query, but not write operations.

How does DAX affect the latency of read requests?

A Increases latency

B Reduces latency from milliseconds to microseconds

C Has no effect

D Only affects write latency

DAX reduces read latency significantly by serving data from in-memory cache.

What ensures that DAX cache stays consistent with DynamoDB data?

A Automatic cache invalidation on data changes

B Manual cache clearing by users

C DAX does not keep cache consistent

D Scheduled daily cache refresh

DAX automatically invalidates or updates cached data when DynamoDB data changes to maintain consistency.

If you write new data to DynamoDB, when will it appear in DAX cache?

A Immediately after write

B After manual cache refresh

C Never, DAX does not cache writes

D When the next read request happens and cache updates

DAX updates its cache on read requests after data changes, ensuring fresh data is served.

Explain what DAX is and how it helps improve DynamoDB performance.

Think about how caching works in everyday apps to make things faster.

Describe how DAX handles data consistency when DynamoDB data changes.

Consider how a cache stays fresh when the original data changes.