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Apache Flink articles

Apache Flink streaming on Iceberg — checkpoint tuning, write optimization, streaming compaction, and real-time lakehouse patterns.

7 articles

Apache Iceberg V3 for streaming — row-level lineage, schema evolution, and governance
Apache IcebergStreamingData GovernanceLakeOps

Apache Iceberg V3 for Streaming: Row-Level Lineage, Schema Evolution, and Governance

Iceberg V3 brings row-level lineage, default column values, and deletion vectors — the features streaming pipelines need for governance without downtime. How V3 changes the streaming governance story on Flink, Kafka, and CDC sources.

Rob M
Rob M
26 min read
The streaming lakehouse — real-time data pipelines on Apache Iceberg without duplication
Data PlatformsApache Icebergstreaming lakehouseApache Flink

Streaming Lakehouse on Apache Iceberg: Kafka, Flink, and Real-Time Pipelines Without Duplication

Build a streaming lakehouse on Apache Iceberg — unify Kafka/Flink ingestion and batch analytics without duplicating data. Production patterns, maintenance reality, and how to keep streaming Iceberg tables performant.

Jonathan Saring
Jonathan Saring
27 min read
Apache Iceberg Commit Conflicts — causes, prevention, and recovery with concurrent write paths
Apache IcebergStreamingApache FlinkCompaction

Apache Iceberg Commit Conflicts: Causes, Prevention, and Recovery

Every concurrent write to an Apache Iceberg table risks a commit conflict. This guide covers how Iceberg's optimistic concurrency works, what triggers CommitFailedException, the common conflict scenarios in streaming and maintenance workloads, and the strategies — from partition isolation to branch-based writes — that eliminate conflicts in production.

Chris P
Chris P
33 min read
Kafka to Iceberg Compaction — Kafka events streaming into an Iceberg table, compacted through a gear process into optimized blocks.
CompactionApache IcebergApache KafkaStreaming

Kafka to Iceberg Compaction — Done Right

Streaming from Kafka into Apache Iceberg creates small files faster than any other write pattern. This guide covers why standard compaction approaches fail for streaming tables, how to measure compaction need, implement partition-aware compaction that avoids writer conflicts, tune rewriteDataFiles parameters, and run maintenance autonomously at scale.

Rob M
Rob M
26 min read
Kafka to Iceberg Ingestion Guide — Kafka logo with streaming data records flowing into a geometric iceberg lakehouse.
Apache IcebergApache KafkaApache FlinkApache Spark

Kafka to Iceberg: Ingestion Guide

A practical guide to streaming data from Apache Kafka into Apache Iceberg tables — covering Kafka Connect, Apache Flink, Spark Structured Streaming, and CDC with Debezium. Includes configuration examples, schema management, partitioning strategies, production pitfalls, and how to keep streaming tables healthy at scale.

Rob M
Rob M
28 min read
Apache Iceberg with Flink Optimization — Flink squirrel mascot with streaming data flowing through an optimization ring into a geometric iceberg, with performance metric icons
Apache IcebergApache FlinkStreamingCompaction

Apache Iceberg with Flink: Streaming Optimization Guide

Flink streaming into Iceberg creates thousands of small files per hour. This guide covers checkpoint tuning, write distribution modes, Flink SQL patterns, and why external maintenance is essential for production streaming tables.

Chris P
Chris P
15 min read
Fixing Small Files in Apache Iceberg — scattered small data cubes compacted into larger organized file blocks flowing toward a geometric iceberg
CompactionApache IcebergLakeOpsApache Flink

Fixing Small Files in Apache Iceberg: A Practical Guide

Small files silently degrade every Apache Iceberg lakehouse — inflating S3 costs, slowing query planning, and bloating metadata. This guide covers root causes, measurement, manual and automated fixes, and how to eliminate the problem at scale.

Rob M
Rob M
19 min read