The Hotels Network simplifies operations, enabling better customer experiences

Challenge

Performance issues and complex API management

A hotel stay is all about unique and unforgettable experiences, and that experience begins from the moment of booking. Hotels always seek to streamline their booking processes, and The Hotels Network (THN) offers tools to attract, engage, and convert visitors. From products like Predictive Personalization to BenchDirect (THN’s flagship product), their customers can set up solutions anytime, anywhere, and benchmark key metrics that impact their online bookings.

With over 20,000 hotels worldwide relying on their services, THN wanted to combine real-time data with their machine learning models to unlock rich opportunities for hoteliers.

"We wondered: what if data were ingested and analyzed in real time so hoteliers could follow their results live? How are we performing this Black Friday? Are the new rates affecting bookings? Not to speak of the new possibilities this could unfold,” says Guillem Solé Bonet, Senior Data Engineer at The Hotels Network.

To make this happen, THN needed to update its infrastructure to tap into real-time data, but the company lacked in-house expertise to maintain its Kafka cluster. The team was also burdened with data latency issues, the complexity of their Kafka instance, and climbing infrastructure costs.

To minimize inefficiencies and maximize performance, THN chose Redpanda for its ability to seamlessly enrich their ML algorithms with real-time data at impressive speed and at a cost-competitive price.

Why Redpanda

Redpanda provides low latency at a fraction of the cost

THN selected Redpanda Cloud over its competitors for several reasons:

• Total compatibility with a wide range of Kafka APIs
• Swift and easy integration with existing infrastructure
• Processes high data volumes with lower latency than other Kafka cloud services
• Cost-effective compute resources, reducing THN’s heavy infrastructure spend

Benchmarks showed 2-3x times lower end-to-end latency than competing Kafka solutions, while enforcing strict durability guarantees across different workload profiles. Redpanda also runs on three times fewer compute resources than Kafka, leading to significant cost savings.

“Redpanda offers a low-latency streaming platform without operational complexity. It also reduces our infrastructure spend and maintenance requirements,” Carrasco says.

THN wasted no time setting up a dedicated cluster in Redpanda, and the deployment process was quick and simple. The company integrated Redpanda with TinyBird to enable real-time analytics. They also adopted Redpanda Console to explore real-time data through a single pane of glass. This feature enables them to swiftly spot and debug problems, and when they need high-level feedback on their architecture or low-level distributed systems expertise, they can rely on Redpanda's Customer Success team for 24/7 support.

By handing the reigns to the Redpanda team, THN no longer needed to spend countless hours struggling with its infrastructure.

"It's easy to work with the Redpanda team — they’re incredibly proactive and fast at problem-solving. Anytime we need something, we know we can turn to Redpanda." — Víctor Carrasco, CTO at The Hotels Network

Results

Harnessing real-time data without the complexity

Redpanda made it easy to switch to real-time streaming data by providing a platform that’s fully compatible with Kafka APIs and also integrated seamlessly with THN’s streaming analytics database, Tinybird. With Redpanda’s lean yet powerful platform, THN solved its data latency issues while minimizing the complexity of building scalable solutions.

"I would recommend Redpanda to any organization requiring high performance, scalable solutions, as well as real-time data streaming and processing. We've had almost 100% uptime since beginning our partnership. We’re very impressed," Carrasco says.

With high volumes of data streamed in real time, THN can improve its machine learning algorithms faster and create new opportunities for hotels to make data-driven decisions.

Moving to Redpanda also freed THN's engineers from tedious and expensive operations and maintenance. Instead, they can focus on upgrading the user experience and developing new products for thousands of hotels around the globe.

Today, THN has expanded its Redpanda Dedicated cluster in AWS and has increased its capacity to build more solutions, application software, and data pipelines for millions of users worldwide.