Kinesis Data Streams Vs Kinesis Data Firehose | Overview.

Kinesis Data Streams Vs  Kinesis Data Firehose - Overview.

Scope:

• Intro,
• Kinesis Data Streams (KDS),
• Kinesis Data Firehose
• When to use which,
• Key Features,
• Example Use Case,
• Quick Comparison Table,
• Final Takeaway.

Intro:

• Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose are both services in AWS.
• Both services are used for ingesting data streams, processing and delivering the streaming data to AWS services or third-party Services.

• But, they serve different use cases and levels of complexity.

 Kinesis Data Streams (KDS)

• A real-time, fully managed, low-latency streaming service designed for  processing.

Used When twtech Needs:

•         Real-time (sub-second) data processing.
•         To build custom applications (e.g., analytics, anomaly detection).
•         Fine-grained control over data processing and throughput.
•         Integration with AWS Lambda, Kinesis Data Analytics, or custom consumers via Kinesis Client Library (KCL).

 Key Features:

•         Manual scaling or auto-scaling (via enhanced fan-out and on-demand mode).
•         Up to 7 days data retention (default is 24 hours).
•         Custom retry logic and multiple consumers.

 Example Use Case:

• A fraud detection system that processes transaction events in real-time using custom logic and machine learning models.

 Kinesis Data Firehose

• A fully managed, near real-time streaming ingestion service designed for simple, automatic delivery to AWS destinations.

Used When twtech Needs:

•         A no-code/no-maintenance way to load streaming data into S3, Redshift, OpenSearch, or 3rd-party tools.
•         Simple data transformation via AWS Lambda or built-in format conversion (e.g., JSON → Parquet).
•         Near real-time processing (latency: 1–60 seconds).

 Key Features:

•         Automatic scaling.
•         Built-in data transformation, compression, and encryption.
•         No need to write consumer code.

 Example Use Case:

• Streaming website logs directly to an S3 bucket in compressed format for later analysis with Athena.

 Quick Comparison Table:

Feature	Kinesis Data Streams	Kinesis Data Firehose
Latency	Sub-second	~1 min
Custom Processing	Yes (Lambda, KCL, custom apps)	Minimal (Lambda transform optional)
Data Retention(storage)	24h–7d	No retention (delivers immediately)
Delivery Targets	Custom apps, KDA, Lambda, etc.	S3, Redshift, OpenSearch, 3rd party
Scalability	Manual or auto-scaling	Fully managed and auto-scaling
Complexity	Higher	Lower (plug-and-play)
Cost	Pay-per-shard	Pay-per-GB ingested

twtech Final Takeaway:

•        Kinesis Data Streams is used if twtech needs real-time, custom processing. 
•        Kinesis Data Firehose is used  if  twtech needs simplified delivery to AWS services with minimal operational overhead.