Victoria Bukta

A factory detects an equipment anomaly and needs the alert in seconds. A financial platform needs to process a transaction, enrich it with account history, and flag it for fraud—all before the customer closes the app. These workloads both involve streaming data, but they have very different requirements under the hood. This session introduces the two core streaming capabilities on Databricks, Real-Time Mode and Zerobus Ingest, and how to match them to your workload. Real-Time Mode on Apache Spark™ Structured Streaming is for when data needs to be acted upon, not just stored. With sub-second, event-driven computation and expressive stateful processing via TransformWithState, it's the right choice for operational workloads where latency directly affects business outcomes: live betting platforms, ad attribution pipelines, fraud detection, and real-time personalization. Zerobus Ingest is a Kafka-free ingestion capability that lets applications and devices write event data directly into Delta Lake, no message broker, no compute overhead, governed delivery out of the box. It's designed to move data fast and at scale. It does not process or transform data in flight, and for…

Streaming is evolving—quickly. Modern architectures are eliminating infrastructure sprawl in favor of a direct-to-lakehouse model, eliminating the need for intermediate message buses and the expense of maintaining them. Zerobus Ingest allows you to push data directly to the lakehouse with near real-time writes, high throughput, and support for thousands of concurrent clients. In this demo-packed session, we’ll cover: - How Zerobus works and how to build production-ready pipelines—without the heavy ownership costs of DIY infrastructure. - The latest supported interfaces (e.g., REST, OTel, and Kafka-compatible APIs), as well as new features designed for massive scale (e.g., liquid clustering, JSON variant type support, etc.). - See how global innovators like Joby Aviation and Toyota Motor Corporation have embraced this shift to streamline their real-time architectures. Join us and discover a direct ingestion framework to simplify your stack and accelerate your impact.

In this session, we’ll introduce Zerobus Direct Write API, part of Lakeflow Connect, which enables you to push data directly to your lakehouse and simplify ingestion for IOT, clickstreams, telemetry, and more. We’ll start with an overview of the ingestion landscape to date. Then, we'll cover how you can “shift left” with Zerobus, embedding data ingestion into your operational systems to make analytics and AI a core component of the business, rather than an afterthought. The result is a significantly simpler architecture that scales your operations, using this new paradigm to skip unnecessary hops. We'll also highlight one of our early customers, Joby Aviation and how they use Zerobus. Finally, we’ll provide a framework to help you understand when to use Zerobus versus other ingestion offerings—and we’ll wrap up with a live Q&A so that you can hit the ground running with your own use cases.

Learn how Databricks and Confluent are simplifying the path from real-time data to governed, analytics- and AI-ready tables. This session will cover how Confluent Tableflow automatically materializes Kafka topics into Delta tables and registers them with Unity Catalog — eliminating the need for custom streaming pipelines. We’ll walk through how this integration helps data engineers reduce ingestion complexity, enforce data governance and make real-time data immediately usable for analytics and AI.