The Apache Flink stream processing framework has gained significant traction across various industries, including travel and hospitality. With its ability to process large-scale data streams in real-time, Apache Flink has become an essential component in travel and hospitality systems that:
In this article, we explore how Apache Flink is revolutionizing the travel and hospitality industry with real-world use cases from Royal Caribbean, United Airlines, Booking.com, and Salto Systems.
Royal Caribbean cruise line carries over 7 million passengers per year to 1,000+ destinations. Traditionally, passengers relied on daily printed itineraries and long queues for activity registration.
With a Flink-powered mobile app, Royal Caribbean transformed the passenger experience by providing:
Flink’s real-time data processing capabilities ensured low-latency synchronization between ship and shore, even when internet connectivity was unstable. This provided a smooth digital experience for passengers and operational efficiency for Royal Caribbean.
Learn more about Royal Caribbean’s digital transformation
United Airlines serves over 50,000 passengers across 4,000+ daily flights. Many customers seek support on social media platforms like X (formerly Twitter). To address this demand, United Airlines implemented a real-time AI-driven chatbot powered by Apache Flink.
United Airlines required real-time processing at scale to identify and respond to customer issues instantly. Flink’s stateful stream processing and windowing features made this automation seamless.
Read more about real-time AI in travel
With over 1 billion room-nights booked per year, Booking.com is a prime target for fraudulent activities such as unauthorized bookings, payment fraud, and loyalty program abuse.
To combat this, Booking.com deployed Apache Flink to power its real-time fraud detection system.
Booking.com needed a high-scale, real-time analytics solution. Flink’s fault tolerance and stream processing speed enabled the security team to detect and mitigate fraud within 10 seconds of an event in 99.9% of cases.
Watch how Booking.com secures travel bookings
Salto Systems, a global leader in smart-lock technology, monitors over 5 million lock events daily across 500,000 hotel rooms worldwide. Their system enables:
Flink’s event-driven processing and scalability allow Salto Systems to handle continuous IoT data streams, ensuring real-time security and operational insights.
🔗 Discover how Salto Systems enhances hotel security
The travel industry operates in a fast-paced, data-intensive environment where real-time decisions are crucial. Apache Flink’s stateful stream processing enables companies to:
Real-time data processing requires end-to-end observability to prevent downtime, errors, or security threats. Datorios provides a comprehensive observability platform for Apache Flink, ensuring:
Want to enhance Flink observability for your travel systems? Explore Datorios Today!
If you’re like most organizations, you currently have real-time data processing projects built, under construction, or planned. The
Introduction At Datorios, we are always pushing boundaries to empower real-time data processing at scale. Today, we are
Apache Flink is a powerful, open-source stream processing framework for real-time and batch data processing. Flink-as-a-Service operations provide
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