What It Is
Sources may include applications, databases, sensors, or APIs; destinations include warehouses, lakehouses, and machine learning models. Typical steps are ingestion, validation, cleaning, enrichment, transformation, and loading. Pipelines can run in batch mode or as continuous streams, depending on how quickly the data is needed.
Key Points
- Batch pipelines: process data in scheduled chunks.
- Streaming pipelines: process events continuously as they arrive.
- Reliability: safe retries without creating duplicates.
- Visibility: monitoring and alerting expose problems early.
Why It Matters
Poorly built pipelines become fragile, and teams spend more time repairing them than using the data they deliver. Reliable design also means scaling with data volume and recovering gracefully from failures.
How ClearLeaff Applies It
We build pipelines that handle more than one million events per second with sub-50ms end-to-end latency, using Apache Kafka and Apache Flink. Observability, quality checks, and governance are included from the start.