Modern enterprises need data platforms that can handle both real-time ingestion and analytical storage without complex integration layers. In this session, we introduce Ursa, a high-performance streaming engine built on Apache Pulsar, designed to unify streaming and lakehouse architectures.

You’ll learn how Ursa bridges Pulsar’s low-latency event streams with modern lakehouse systems, enabling seamless, efficient writes from topics directly into analytical storage — transforming streaming data into queryable tables in real time.

Key highlights:

• Inside Ursa’s architecture: Combining Pulsar’s scalability with the durability and structure of lakehouse storage.
• Two integration modes:
  • Managed Tables — lightweight, internally managed storage for quick access.
  • External Tables — writes data to external lakehouses with open catalog registration.
• Support for Databricks Unity Catalog, Snowflake’s Open Catalog, and Open S3Table format.
• Handling schema evolution, efficient file writing (e.g., Parquet optimization), and table registration for seamless downstream analytics.
• Real-world insights into building cloud-native, unified lakehouse pipelines powered by Ursa and Pulsar.

Whether you’re architecting real-time pipelines, modernizing your lakehouse, or looking to simplify your streaming-to-analytics stack, this talk provides the blueprint for achieving a truly unified data platform.