Apache Flink
Apache Flink is a advanced techniques concept in the Data Engineering pillar.
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View full graph →Apache Flink is a advanced techniques concept in the Data Engineering pillar.
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Explain Apache Flink as if teaching a colleague who is new to advanced techniques. Cover: what it is, how it works, and why it matters.
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A diagram for Apache Flink should include: 1. The core components of apache flink 2. How they interact 3. Expected outcomes or outputs
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Delta Lake vs Apache Iceberg vs Apache Hudi: Lakehouse Format Shootout
Head-to-head comparison of the three major lakehouse storage formats: table mutation semantics, time travel, schema evol
Debezium and CDC: Capturing Database Changes at Scale
Change Data Capture with Debezium: connector configuration, schema evolution handling, initial snapshots, and integratio
Apache Iceberg Deep Dive: Table Formats for the Lakehouse Era
How Apache Iceberg enables ACID transactions on data lakes: partitioning, hidden partitioning, time travel, snapshot iso
Real-Time Streaming with Apache Kafka: From Pub/Sub to Event-Driven Architecture
Production patterns for Apache Kafka: topic design strategies, consumer group rebalancing, exactly-once semantics, Kafka
Streaming ETL for Suspicious Activity Reports: Real-Time AML Data Pipelines with Kafka and Flink
Architecture patterns for building real-time AML surveillance data pipelines using Apache Kafka for transaction ingestio
DataOps Trends & Tool Landscape 2026
Current trends in DataOps: medallion architecture, Dagster vs Airflow, data contracts, Apache Iceberg, and quality-as-co
Exactly-Once Semantics in Stream Processing
How Kafka + Flink/Spark achieve exactly-once processing: idempotent producers, transactional log offsets, and checkpoint