How to Implement Caching Mechanism for DynamoDB to Improve Performance and Reduce Costs
Question
One of your clients has a web application hosted on-prem and has recently migrated its database service to DynamoDB.
The application receives more than 1000 read requests per second compared to 200 write requests every second.
The client has asked you to implement a caching mechanism to speed up the read requests and save costs on RCUs.
What changes are needed to make it work?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: B.
DAX (DynamoDB Accelerator is a dedicated service designed to cache DynamoDB requests.
It will automatically add the data in DAX if there's a cache miss or update the data if it is updated in the table).
A is incorrect: You can implement the ElastiCache redis cluster.
But that will require additional overhead compared to DAX.
You will have to manually write data to redis cluster in case of a cache miss and update the data in the cluster in case of data update in DynamoDB.
DAX is a better option compared to ElastiCache hence this is an invalid choice.
C is incorrect: The same applies with Memcached cluster as well.
Additional overhead like redis cluster.
D is incorrect: Because option B is the correct answer, this is an invalid choice.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DAX.htmlThe correct answer is A. Create an ElastiCache Redis cluster and configure your application to write the most frequently accessed data to Redis for faster read queries.
Explanation:
DynamoDB is a highly scalable NoSQL database service provided by AWS. It provides fast and predictable performance with seamless scalability. It is designed to handle high traffic applications, but it can become costly if the application receives too many read requests. To reduce the cost of RCUs and to speed up the read requests, a caching mechanism can be implemented.
Amazon ElastiCache is a managed in-memory caching service provided by AWS. It is a cost-effective solution to improve the performance of web applications by reducing the load on the database. ElastiCache supports two popular open-source in-memory caching engines, Redis and Memcached.
Redis is a popular in-memory data structure store that can be used as a database, cache, and message broker. It provides fast read and write operations and supports advanced data types such as sets, hashes, and lists. Redis can be used to cache the most frequently accessed data, which can significantly reduce the number of read requests to DynamoDB, hence saving on RCUs.
Option A is the correct answer because it suggests creating an ElastiCache Redis cluster and configuring the application to write the most frequently accessed data to Redis for faster read queries. This approach will help reduce the load on the database and improve the performance of the application.
Option B suggests placing a DynamoDB accelerator in front of the database to cache frequently accessed data. DynamoDB accelerator, also known as DAX, is a caching layer that sits between the application and DynamoDB. It can help improve the performance of read-heavy applications by reducing the number of requests to DynamoDB. However, DAX can be costly and is not recommended for applications with a small number of read requests.
Option C suggests placing an ElastiCache Memcached cluster in front of DynamoDB to cache the requests. Memcached is another in-memory caching engine that supports key-value data types. However, Memcached does not support advanced data types like Redis, and it is not recommended for applications that require complex data structures.
In conclusion, Option A is the correct answer as it suggests using an ElastiCache Redis cluster to cache frequently accessed data and reduce the load on the database.
