A company needs to have a data store in AWS. The company is responsible to getting weather data and then performing the required analysis on the data. The amount of data can go into Petabytes. It needs to be ensured that storage is efficient when it comes to storage of sparse data. Which of the following would be the MOST ideal data store?

Answer options:

A.AWS Redshift
B.AWS EMR with HBase
C.AWS RDS
D.AWS DynamoDB

Answer – B
This is mentioned in one of the whitepapers
For large datasets, such as log data, weather data, product catalogs, and so on, you might already have large amounts of historical data that you want to maintain for historical trend analysis, but need to ingest and batch process current data for predictive purposes. For these types of workloads, Apache HBase is a good choice because of its high read and write throughput and efficient storage of sparse data
Option A is incorrect since this is used for data warehousing purposes
Option C is incorrect since this is used for OLTP types of databases
Option D is partially correct but here EMR with Hbase is better
For more information on DynamoDB vs HBase, please refer to the below URL
https://d1.awsstatic.com/whitepapers/AWS_Comparing_the_Use_of_DynamoDB_and_HBase_for_NoSQL.pdf