Question

Kinesis Data Streams vs Firehose - who does scaling differ?

(A) Kinesis Data Streams
(B) Kinesis Data Firehose
(C) Both A and B
(D) None of the above

Answer 1

Kinesis Data Streams requires manual scaling by adjusting the number of shards, whereas Kinesis Data Firehose scales automatically to handle incoming data loads.

Step-by-step explanation:

When discussing the scaling capabilities of Kinesis Data Streams versus Kinesis Data Firehose, it is important to understand that these services are designed to handle data stream workloads in different ways. With Kinesis Data Streams, scaling is a manual process. Users have to adjust the number of shards in a stream to accommodate the throughput requirements, where each shard has a certain capacity in terms of data ingestion and read transactions. In contrast, Kinesis Data Firehose automatically scales to accommodate incoming data loads without manual intervention. This makes Kinesis Data Firehose a more hands-off service when it comes to scaling up or down.

So, in terms of who handles scaling differently, the correct answer would be:

(A) Kinesis Data Streams