Many large-scale, data-heavy systems—especially in regulated industries like finance or pricing—face a difficult trade-off: the more complex and compliant the system, the higher the infrastructure and operational cost. But with the right architectural choices, complexity doesn’t have to mean inefficiency.
In this session, we explore how to design cost-efficient architectures for complex data domains without compromising performance or compliance. Using real-world use cases from a pricing domain, we’ll identify the major cost drivers in data systems and show how choosing the right technologies early in the design phase can lead to massive savings down the road.
What you’ll learn:
- Key factors influencing cost in complex data architectures.
- How to leverage **URSA, a Kafka-compatible streaming engine that writes directly to Apache Icebergand Delta Lake, **to unify event ingestion and delivery.
- How Apache Flink’s stream processing powers real-time computation with minimal overhead.
- How RisingWave’s continuous joins and ad-hoc queries enable efficient real-time analytics without duplicating data.
- Practical design patterns for building elegant, scalable, and cost-effective streaming architectures.
If you’re an architect, engineer, or decision-maker balancing cost, complexity, and compliance, this talk offers practical insights into how to build smarter — not just bigger — data systems.
