Writing My First DataHarness Blog Post! | Personal Projects With Ex-Google SWE, Ep 12
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A developer (ex-Google SWE) walks through the first blog post for their personal project called DataHarness — a composable data layer designed to unify multiple data sources (Kafka, PostgreSQL, Iceberg, DuckLake) with transactional exactly-once semantics. The post covers Apache Iceberg's limitations (concurrent write conflicts, small file overhead, equality delete inefficiency), existing mitigation technologies (Hudi, Flink, Kafka Connect, DuckLake, Paimon), and how DataHarness aims to provide a generalizable abstraction layer with distributed locking, atomic schema evolution, consistent read snapshots, and fine-grained partitioning. Four pipeline examples are presented ranging from simple Kafka-to-Iceberg buffering to horizontally sharded multi-partition pipelines using Apache Paimon.