Get Kafka-Nated S2E1: Giannis Polyzos on Fluss, Lakehouse, and the Future of Streaming

Season 2 of Get Kafka-Nated kicks off with Giannis Polyzos, member of the Fluss PMC, for a deep dive into one of data infrastructure’s longest-running debates: streaming vs. batch, or both? What we’ll cover: - What Fluss is and the problems it aims to solve - Streaming vs. batch: why the debate isn’t either/or anymore - How Fluss fits into modern lakehouse architectures - Where lakehouses and streaming platforms are headed over the next few years - What this evolution means for data engineers and platform teams Timestamps: 02:20 – What Is Apache Fluss and Why It Exists 05:30 – Streaming, Batch, and the Lakehouse Evolution 10:30 – Tables vs Topics: Rethinking Core Abstractions 15:40 – Apache Paimon, Iceberg, and Data Continuity 20:15 – Real-World Architectures and Stream-Batch Unification 25:45 – Streaming, AI, and Centralized Data for ML Pipelines 30:45 – Spark, Flink, and the Fluss Ecosystem 34:50 – Why Streaming Is Still Underrated Useful links: - Get Kafka-Nated playlist: https://www.youtube.com/@Aiven/playlists - Offical Fluss website: https://fluss.apache.org/ - Aiven blog ‘Streaming data analytics in the real world’: https://aiven.io/blog/streaming-data-analytics-in-the-real-world #ApacheKafka #StreamingData #Lakehouse #DataEngineering #Aiven