SystologyStreaming
- 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.
- Intervals & Constraints
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Analytics
,
Data-Pipelines
,
Integrity
and +1 more
A framework for balancing Latency (system Completeness) against Verification (data Integrity) by effectively choosing between Speculative execution and Pessimistic consensus intervals.
- 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.