Streaming data with Apache Kafka® has become the backbone of modern day applications. While streams are ideal for continuous data flow, they lack built-in querying capability. Unlike databases with indexed lookups, Kafka's append-only logs are designed for high throughput processing, not for on-demand querying. This necessitates teams to build additional infrastructure to enable query capabilities for streaming data. Traditional methods replicate this data into external stores such as relational databases like PostgreSQL for operational workloads and object storage like S3 with Flink, Spark, or Trino for analytical use cases. While useful sometimes, these methods deepen the divide between operational and analytical estates, creating silos, complex ETL pipelines, and issues with schema mismatches, freshness, and failures.\n\nIn this session, we’ll explore and see live demos of some solutions to unify the operational and analytical estates, eliminating data silos. We’ll start with stream processing using Kafka Streams, Apache Flink®, and SQL implementations, then cover integration of relational databases with real-time analytics databases such as Apache Pinot® and ClickHouse. Finally, we’ll dive into modern approaches like Apache Iceberg® with Tableflow, which simplifies data preparation by seamlessly representing Kafka topics and associated schemas as Iceberg or Delta tables in a few clicks. While there's no single right answer to this problem, as responsible system builders, we must understand our options and trade-offs to build robust architectures.

This isn't your typical tech talk—it's a story of the journey into how big players like LinkedIn, Uber Eats, and Stripe are mastering the art of real-time data. Viktor is here to demystify Apache Pinot's superpowers, showing you how it instantly transforms mountains of data into actionable insights. Business decision-makers have long had access to dashboards and reports, but now analytics can be made available to users as features of stickier, more engaging applications. With stories, insights, and a touch of humor, Viktor will unpack the cool features of Apache Pinot, including the Star-Tree Index, and show you why it’s a game-changer in data strategy. This session is for everyone, whether you're a data geek, a business guru, or just curious about the future of tech. Viktor's dynamic style will keep you on the edge of your seat, eager to implement these insights. So, buckle up and get ready to be wowed by the power of real-time analytics with Apache Pinot – it will be a blast!

Explore how industry leaders like LinkedIn, Uber Eats, and Stripe are mastering real-time data with Viktor as your guide. Discover how Apache Pinot transforms data into actionable insights instantly. Viktor will showcase Pinot's features, including the Star-Tree Index, and explain why it's a game-changer in data strategy. This session is for everyone, from data geeks to business gurus, eager to uncover the future of tech. Join us and be wowed by the power of real-time analytics with Apache Pinot!

Master the wicked-fast Apache Kafka streaming platform through hands-on examples and real-world projects. In Kafka in Action you will learn: Understanding Apache Kafka concepts Setting up and executing basic ETL tasks using Kafka Connect Using Kafka as part of a large data project team Performing administrative tasks Producing and consuming event streams Working with Kafka from Java applications Implementing Kafka as a message queue Kafka in Action is a fast-paced introduction to every aspect of working with Apache Kafka. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to produce and consume streams of events. Advancing quickly, you’ll soon be ready to use Kafka in your day-to-day workflow, and start digging into even more advanced Kafka topics. About the Technology Think of Apache Kafka as a high performance software bus that facilitates event streaming, logging, analytics, and other data pipeline tasks. With Kafka, you can easily build features like operational data monitoring and large-scale event processing into both large and small-scale applications. About the Book Kafka in Action introduces the core features of Kafka, along with relevant examples of how to use it in real applications. In it, you’ll explore the most common use cases such as logging and managing streaming data. When you’re done, you’ll be ready to handle both basic developer- and admin-based tasks in a Kafka-focused team. What's Inside Kafka as an event streaming platform Kafka producers and consumers from Java applications Kafka as part of a large data project About the Reader For intermediate Java developers or data engineers. No prior knowledge of Kafka required. About the Authors Dylan Scott is a software developer in the insurance industry. Viktor Gamov is a Kafka-focused developer advocate. At Confluent, Dave Klein helps developers, teams, and enterprises harness the power of event streaming with Apache Kafka. Quotes The authors have had many years of real-world experience using Kafka, and this book’s on-the-ground feel really sets it apart. - From the foreword by Jun Rao, Confluent Cofounder A surprisingly accessible introduction to a very complex technology. Developers will want to keep a copy close by. - Conor Redmond, InComm Payments A comprehensive and practical guide to Kafka and the ecosystem. - Sumant Tambe, Linkedin It quickly gave me insight into how Kafka works, and how to design and protect distributed message applications. - Gregor Rayman, Cloudfarms