Parallelization
- Data Pipelines
—
data-pipelines
,
fault-tolerance
,
parallelization
and +2 more
Architectural principles for reliable batch and streaming data pipelines; focusing on strict time semantics, exactly-once processing, optimal partitioning, observability, and reproducible states.
- Data Processing Architectures
—
data-pipelines
,
fault-tolerance
,
parallelization
and +2 more
A deep architectural comparison of data processing pipelines: evaluating Apache Spark's batch ETL model against Apache Beam's portable unified model and Apache Flink's native API for stateful processing.