A large multi-media company is hosting their application on AWS.
The application is currently using DynamoDB table for storage and retrieval of data.
The data access for items in the table is currently in milliseconds, but the company wants to improve further on the access times.
How can this be achieved?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer - D.
The AWS Documentation mentions the following.
Amazon DynamoDB is designed for scale and performance.
In most cases, the DynamoDB response times can be measured in single-digit milliseconds.
However, certain use cases require response times in microseconds.
DynamoDB Accelerator (DAX) delivers fast response times for accessing eventually consistent data for these use cases.
Option A is incorrect because using a larger table means providing more capacity, which does not help improve access times.
Options B and C are incorrect because the read and write capacities specify the number of reads and writes per second required for the application.
This does not help to improve the access time.
For more information on DynamoDB Acceleration, please refer to the below URL-
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DAX.htmlThe best solution to further improve the access times of a DynamoDB table for a large multimedia company is to make use of the DAX (DynamoDB Accelerator) feature, which is a fully managed, highly available, and in-memory cache for DynamoDB. DAX is designed to improve the read performance of DynamoDB tables by caching frequently accessed data in memory.
DAX reduces the response times of read-heavy workloads by caching data and storing it in memory, thereby eliminating the need to repeatedly query the database. This reduces the read latencies and improves the response times for read requests. DAX can handle millions of requests per second, making it ideal for applications that need to deliver fast and consistent read performance.
Using larger DynamoDB tables does not necessarily improve access times, as the size of the table does not have a direct impact on performance. The table's read and write capacity, on the other hand, affects the table's ability to handle requests. Increasing the read or write capacity on the table will increase the number of requests that can be processed concurrently, but it will not necessarily improve access times.
In summary, to improve the access times of a DynamoDB table for a large multimedia company, it is best to use the DAX feature. DAX reduces the read latencies by caching frequently accessed data in memory, thereby improving the response times for read requests.