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