Name: Data Stream Night
Start: 2024-09-16T16:00:00-07:00
End: 2024-09-16T19:00:00-07:00
Location: Atelier 1205

**Agenda**

CST Time
6:00-6:30 Networking
6:30-7:30 Tech Talks
Yingjun Wu (CEO at RisingWave) - How to Process Streaming Data: An Unbiased Guide
Sijie Guo (CEO at StreamNative) - Ursa: Kafka-compatible data streaming on Lakehouse
7:30-8:00 Networking
8:00-8:30 Book Signing
Streaming Databases by Hubert Dulay and Ralph Debusmann
8:30-9:00 Networking

**Tech Talks - Abstract and Bios**
*How to Process Streaming Data: An Unbiased Guide*
Abstract: (will be shared soon)
Bio: Yingjun Wu is the founder of RisingWave Labs. Before starting the company, Yingjun was a software engineer at the Redshift team, AWS, and a researcher at the Database group, IBM Almaden Research Center. Yingjun received his PhD degree from the National University of Singapore and was a visiting PhD at Carnegie Mellon University.

*Ursa: Kafka-compatible data streaming on Lakehouse*
Abstract: Ursa is a Kafka-compatible data streaming engine built on top of a lakehouse, enabling users to store their topics and associated schemas directly in lakehouse tables. Ursa utilizes the innovations that StreamNative has developed to evolve Pulsar's storage layer from a disk-based shared storage layer to an object storage-based tiered storage system and to integrate with the lakehouse ecosystem. The Ursa engine simplifies the integration between data streams and lakehouse tables, drastically reducing the complexity of using bespoke integrations. In this talk, we will dive deeper into the details of the Ursa engine and how it leverages the lakehouse as a storage backend.
Bio: Sijie is one of the original creators of Apache Pulsar and the Co-founder and CEO of StreamNative. His journey with data streaming began at Yahoo! and he also led a messaging infra team in Twitter. In 2017 he co-founded Streamlio which was acquired by Splunk and in 2019 he founded StreamNative.

**Book Signing**
*Streaming Databases by Hubert Dulay and Ralph Debusmann*
Real-time applications are becoming the norm today. But building a model that works properly requires real-time data from the source, in-flight stream processing, and low latency serving of its analytics. With this practical book, data engineers, data architects, and data analysts will learn how to use streaming databases to build real-time solutions.
Authors Hubert Dulay and Ralph M. Debusmann take you through streaming database fundamentals, including how these databases reduce infrastructure for real-time solutions. You'll learn the difference between streaming databases, stream processing, and real-time online analytical processing (OLAP) databases. And you'll discover when to use push queries versus pull queries, and how to serve synchronous and asynchronous data emanating from streaming databases.

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Data Stream Night 

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Atelier 1205

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Data Stream Night

Real-Time Data + AI San Francisco

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