Kinesis Data Streams vs Firehose

Joshua Callis

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Apr 17, 2023

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Kinesis Data Streams

• Must write custom code for producer and consumers.
• Real time (200ms latency for classic and 70ms latency for enhanced fan-out — i.e aggregating the shards).
• Must manage autoscaling via shard splitting / merging.
• Data storage for 1–365 days, able to replay data.
• KPL (Kinesis Producer Library) can produce information into either Data Streams or Firehose.
• If you require applications to Continuously read data in real time. Kinesis Data Streams would be a good use case.
• More detailed information can be found here: https://joshuajordancallis.medium.com/kinesis-data-streams-in-a-nutshell-b9330f6209b6

Firehose

• Fully managed service, to send data to a destination such as S3, Redshift etc.
• Near real-time.
• Automated Scaling.
• No data storage.
• Serverless.
• If all you need to do is send data to various destinations, Firehose would be a good use case.
• More detailed information can be found here: https://joshuajordancallis.medium.com/kinesis-data-firehose-b0963991c304