Laminar vs Apache Flink

Both are powerful stream processing engines. Here's how Laminar simplifies your data pipeline while reducing costs by 60-80%.

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Key Differences

No Kafka Required

Laminar has built-in durability. Flink requires Kafka for exactly-once semantics.

Native Iceberg

Direct write to Iceberg with automatic compaction. No separate sink connector needed.

Zero Ops

No state backend, checkpointing, or task manager configuration required.

60-80% Lower Cost

Rust-based engine with lower memory footprint. No Kafka infrastructure costs.

Architecture Comparison

Flink requires multiple components for a production pipeline. Laminar replaces them with a single, integrated solution.

Apache Flink Stack

Traditional CDC Pipeline

PostgreSQL/MySQLDebeziumKafkaFlinkCompaction JobIceberg
5+ components to manage
Separate compaction jobs
State backend configuration

Laminar

Laminar CDC Pipeline

PostgreSQL/MySQLLaminarIceberg
Single binary deployment
Built-in compaction
Managed state included

Performance Benchmarks

Throughput

Events per second (higher is better)

Flink (Kafka source)500.0K eps
Laminar10.0M eps

End-to-End Latency

Event to queryable in Iceberg

Flink + Iceberg Sink60.0Kms
Laminar1.0Kms

Lower is better

Memory Usage

Per worker node

Flink TaskManager8.0 GB
Laminar Worker2.0 GB

Lower is better

Monthly Infrastructure Cost

10M events/day workload

Flink + Kafka + S35.0K$
Laminar + S3800.0$

Lower is better

No comparison data

When to Use Each

Choose Flink if you need:

  • Complex event processing (CEP) patterns
  • Extensive connector ecosystem
  • Mature, battle-tested technology
  • Custom operators in Java/Scala

Choose Laminar if you need:

  • Fast data ingestion to lakehouse
  • SQL-first pipeline development
  • Minimal operational overhead
  • Lower infrastructure costs
  • Native CDC without Debezium

Easy Migration from Flink

Most Flink SQL queries work directly in Laminar. Our team can help you migrate your existing pipelines with minimal changes.

Start Migration Guide

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