Kinesis Producer Library (KPL) vs Kinesis Client Library (KCL) | Overview.

Kinesis Producer Library (KPL) vs Kinesis Client Library (KCL) - Overview. 

Scope:

• Intro,
•  High-Level Overview,
• Kinesis Producer Library (KPL) Concept,
• Kinesis Client Library (KCL) concept
• Features,
• When to use  Kinesis Producer Library (KPL),
• When to use  Kinesis Producer Library
• Limitations,
• Summary Comparison Table,
• When to Use What table.
• Can both KPL & KCL be used

Intro:

• Here's twtech comparison of Kinesis Producer Library (KPL) vs Kinesis Client Library (KCL).
•  Both are essential tools in the Amazon Kinesis ecosystem, but they serve different purposes.

 High-Level Overview

Library	Purpose	Typical Role
KPL (Kinesis Producer Library)	Optimizes writing/producing records to Kinesis Data Streams	Used by producers
KCL (Kinesis Client Library)	Simplifies reading and processing records from Kinesis	Used by consumers

 Kinesis Producer Library (KPL) concept:

• A high-performance Java library (can be used via native and multi-language wrappers) designed to efficiently write data to a Kinesis Data Stream.

 Features:

• Aggregation: Combines multiple logical records into one Kinesis record to reduce API calls and cost
• Retries & Failover: Handles network or throughput exceptions gracefully
• Asynchronous put: High-throughput writes without blocking.
• Time-based buffering: Controls how long records are batched before being sent

 When to use  Kinesis Producer Library (KPL):

• twtech needs high-throughput ingestion
• twtech is writing to Kinesis from Java
• twtech wants to optimize cost and network use

 Limitations:

• Requires a daemon (Java process) to run (if used from non-Java apps)
• More complex deployment than just using the AWS SDK
• Limited to producer role only

 Kinesis Client Library (KCL) concept:

• A Java-based consumer library that helps developers build applications that read from Kinesis Data Streams, manage shard coordination, and checkpoint processing.

 Features:

• Checkpointing (via DynamoDB): Tracks where a consumer left off
• Shard management: Automatically balances shards among multiple workers
• Resharding support: Handles new shards during scaling
• Multi-lang support (via MultiLangDaemon): lets twtech use Python, Node.js, etc.

When to use Kinesis Client Library (KCL):

• twtech needs robust consumer applications
• twtech wants to track state (checkpointing) reliably
• twteeh has multiple parallel consumers

 Limitations:

• Requires DynamoDB table for checkpointing
• Polling-based, so may not be as low-latency as Enhanced Fan-Out
• Not event-driven like Lambda (slightly higher operational overhead)

 Summary Comparison Table

Feature	KPL	KCL
Role	Producer	Consumer
Main Language	Java (Native bindings for others)	Java (with MultiLangDaemon)
Optimized For	Efficient record ingestion	Scalable, stateful record processing
Record Aggregation	✅ Yes	❌ No
Async Writes	✅ Yes	❌ No (polling reads)
Checkpointing	❌ No	✅ Yes (DynamoDB)
Shard Coordination	❌ No	✅ Yes
Fan-Out Support	❌ No	❌ But twtech can use with enhanced fan-out (EFO) separately
Lambda Alternative	❌ No	✅ Possibly (if twtech wants more control than Lambda)
Complexity	Moderate	Higher (more infra: DynamoDB, coordination logic)

 When to Use What

Use Case	Recommendation
twtech is  ingesting 1000s of records/sec efficiently.	KPL.
twtech wants a real-time consumer that handles checkpointing.	KCL.
twtech wants a simple event-driven consumer.	Consider Lambda instead of KCL.
twtech is using non-Java language and doesn’t want extra daemons.	Use AWS SDK (simpler) or Lambda.

 Bonus: Can both KPL & KCL be used

Yes. 

• twtech can use KPL on the producer side and KCL on the consumer side.

NB:

• If KPL aggregates records, twtech KCL consumer must de-aggregate them using the KinesisDeaggregator.
• Kinesis de-aggregation is  the process of extracting individual user records from a single Amazon Kinesis Data Streams record that contains multiple, smaller records initally  bundled together (aggregated) by the Kinesis Producer Library (KPL) to improve throughput.