Om sesjonen
Modern AI and analytics workloads punish architectures built on copying data between systems. In this workshop, we build a vendor-neutral, open-source HTAP stack that combines transactional, analytical, and AI-oriented workloads without the usual ETL tax. The architecture is based on a practical demo stack using Apache Cassandra for operational data, Apache Kafka for ingestion, Apache Spark for large-scale processing, Presto for interactive SQL, and open table and search technologies such as Parquet, Iceberg, and OpenSearch.
Participants will bring up the stack locally, stream events into it, query live operational data, run analytical queries, and export data for downstream use. Along the way, we will discuss why real-time context, cost control, and reducing duplication matter for modern systems, especially when building AI-ready platforms and agent-facing applications.
This is not a product pitch. It is a hands-on architecture workshop for developers and architects who want to understand how open-source building blocks fit together to support low-latency apps, analytics, and AI use cases in one platform.