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Cathay Pacific is evolving beyond aviation, rebranding as Cathay to offer a seamless travel and lifestyle ecosystem. From flights to shopping, loyalty rewards, and digital experiences, real-time data streaming with Apache Kafka is at the heart of this transformation. By replacing traditional middleware with a cloud-native Kafka platform, Cathay has unlocked real-time customer insights, seamless integrations, and smarter operations—driving innovation across the travel industry.

Even digital natives – that started their business in the cloud without legacy applications in their own data centers – need to modernize their cloud-native enterprise architecture to improve business processes, reduce costs, and provide real-time information to their downstream applications. This blog post explores the benefits of an open and flexible data streaming platform compared to a proprietary message queue and data ingestion cloud services. A concrete example shows how DoorDash replaced cloud-native AWS SQS and Kinesis with Apache Kafka and Flink.

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a blog series. This is part 2: Data Streaming for Data Ingestion into the Data Warehouse and Data Lake.