🌊 Data in Motion: Streaming & CDC for AI & Agents

🌊 Data in Motion: Streaming & CDC for AI & Agents
When: 🕠 5:30–8:00 PM (🍽️ dinner included)
⚡ Your agent is only as smart as its context.

To achieve an enterprise-ready real-time data stack for agents, an organization needs to look at data movement end-to-end: 🔄 a stream that moves data from operational sources to analytical targets, 🗄️ a database that can ingest and serve that stream at the speed agents demand, and 🛡️ a way to govern the data as it lands.

Join VeloDB, Redpanda, LaserData and Datastrato for a working session on building that streaming stack: 📥 ingesting at scale, ⏱️ moving data with low latency, 🔍 querying it the second it arrives, and 🛡️ governing it the moment it lands, so your agents always run on the freshest context.
Three short talks, 🍲 dinner, and 🍻 conversation in SF!
✨ Speakers
Real-Time Data Architecture for the Agentic Era
🎤 Peter Corless — Principal Product Marketing Manager, Redpanda
Discover how enterprises are building enterprise-scale agentic AI applications. These real-time responsive systems require several components in their data architecture: event-driven data streaming, real-time analytics engines, and AI-centric application frameworks for governance, trust, and explainability.
Closing the Governance Gap Between the Stream and the Lakehouse
🎤Mark Hoerth — Product Lead & Solutions Architect, Datastrato
Streaming and analytics keep converging, but governance usually doesn't follow the data across the seam. A topic lives in one world with its own access model; the table it becomes lives in another. This talk shows how an open catalog can span both. Using Redpanda's broker-native Iceberg Topics to turn a live stream into an Apache Iceberg table with no ETL, and Apache Gravitino as the catalog of catalogs holding the topic and resulting table in a single metalake, we'll govern data the same way before and after it lands. The session ends with a live walk from produced records to a governed, queryable Iceberg table under one consistent policy. The takeaway: your governance boundary doesn't have to break where your streaming engine hands off to your lakehouse.

Fast In, Fast Out: A Real-Time Analytics Stack with Apache Iggy (Incubating) and Apache Doris
🎤 Kranti, Founder and CEO, LaserData & Kevin Shen, PPM, VeloDB
This talk pairs two open-source projects to build a real-time analytics stack covering both fast ingest and fast queries: Apache Iggy (incubating), LaserData's Rust message-streaming platform that moves high event volumes at very low latency, and Apache Doris (the database behind VeloDB), which serves sub-second queries on fresh data under heavy concurrency, updates, and joins. After a brief intro to each project, the session walks through a Rust-native Iggy sink connector that streams events directly into Doris with no JVM or intermediary systems, then closes with a live demo pushing a real workload through Iggy into Doris and running analytics as the data lands—leaving attendees with an understanding of why real-time analytics needs both halves, how the connector wires them together, and when and how to build the stack themselves.

⚠️ Important: Building Access Required
This event is hosted at the AWS office. You must register at both links to attend:
✅ RSVP here on Luma
✅ Register for building access: AWS Event Registration