
Lightstreamer Hits the Road with Confluent on the Data Streaming World Tour
đ Weâre excited to announce that Lightstreamer is joining Confluent on the Data Streaming World Tour (DSWT)! The tour brings together data streaming experts, practitioners, and technology partners from around the world to share insights, real-world use cases, and the latest innovations in the streaming ecosystem.
As a sponsor of the Milan stop, Lightstreamer will showcase how our technology makes it possible to stream real-time Kafka data directly to mobile and web applicationsâsecurely, reliably, and at scale.
Thursday, 16 October 2025 | 9:00am – 5:00pm
Hotel Principe di Savoia
Piazza della Repubblica, 17, Milan, 20124 – Italy
Why Attend
The Data Streaming World Tour is designed for data architects, developers, and business leaders who want to harness the full power of event-driven architectures. At the Milan event, youâll have the chance to:
â Learn how to overcome Kafkaâs operational challenges and simplify last-mile delivery of data.
â Discover best practices for building reliable, real-time pipelines that power mission-critical applications.
â Explore the latest innovations in stream processing and governance from Confluent and its partners.
â Connect with industry peers and get practical insights you can apply immediately in your projects.
Where Lightstreamer Fits In
Kafka is the backbone of modern data streaming, but when it comes to delivering that data to end-user applicationsâwhether mobile, web, or IoTâorganizations often face new challenges: scalability, latency, security, and resource efficiency.
This is where Lightstreamer comes in. By bridging Kafka with front-end applications, we enable organizations to push real-time data updates to millions of users with ultra-low latency while maintaining operational simplicity.
Secure Your Spot
đ Seats are limited for the Milan stop of the tour, so donât miss your chance to be part of this global event.
We look forward to meeting you in Milan and sharing how Lightstreamer can take your Kafka data from stream to screen..