Weβre excited to announce Data Streaming Summit San Francisco 2025 is returning September 29-30, 2025. This in-person event brings together data streaming enthusiasts, developers, and industry leaders from around the world to connect and share insights.
Do you have a story to share about data streaming technologies like Pulsar, Kafka, or Ursa, or stream processing frameworks like Flink or Spark? This yearβs theme, "Unlocking Real-Time AI," focuses on innovative, insightful, and thought-provoking ideas.
Join us as a speaker and help shape the future of data streaming!
Why Speak at the San Francisco Summit?
As a speaker, you will receive:
π CFP Opens: Thursday, May 29th, 2025
π CFP Closes: Friday, July 18th, 2025
π Speaker Notifications Sent: Friday, July 25th, 2025
π Schedule Announcement: Monday, August 11th, 2025
We invite submissions across the following themes:
πΉ Data Streaming + AI β The convergence of AI and data streaming is reshaping how organizations build intelligent, real-time systems. Share your experience using data streaming technologies to power AI-driven applications, real-time machine learning pipelines, or intelligent automation. How do you ensure trustworthy real-time data for AI assets? What are the best practices for integrating streaming data into AI models?
π Learning Data Streaming (Pulsar, Kafka, Ursa, or more) β Are you passionate about educating others? Submit an entry-level talk introducing Pulsar, Kafka, or Ursa, covering key concepts, architectures, and best practices to help newcomers kick-start their data streaming journey.
π Deep Dive into Data Streaming β For technical experts, we invite advanced discussions on Pulsar, Kafka, Ursa Engine, and cutting-edge architectures such as leaderless streaming, lakehouse-native storage, and real-time data processing optimizations. How do you design scalable, high-performance streaming infrastructures? What challenges have you solved at scale?
π Real-Time Ingestion into the Data Lakehouse β Streaming is the backbone of modern lakehouse ingestion, enabling AI and analytics teams to work with the most up-to-date and trustworthy data. We welcome talks on best practices, challenges, and architectures for integrating real-time streaming with data lakehouses like Delta Lake, Iceberg, and Hudi.
π Unifying Governance and Access with Data Catalogs β As real-time and AI-driven data ecosystems grow, governance and unified access become critical. We invite talks on strategies for bridging real-time streaming with data catalogs and metadata management, ensuring data consistency, security, and AI readiness.
πΏ Stream Processing and Ecosystem β Have you built tools or integrations that enhance Flink, Spark, RisingWave, or other stream processing frameworks? Share your experiences in optimizing event-driven architectures, real-time analytics, and complex streaming pipelines. How do you balance latency, scalability, and cost-efficiency in stream processing?
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