THE CHALLENGE
Scaling a digital ecosystem without limits
In the fast-moving world of digital mobility, consumer expectations are high. Whether paying for fuel at the pump, managing an electric vehicle charging session, or checking home electricity consumption, users demand instant responsiveness. For Klikin, the software company behind Repsol’s flagship app, Waylet, meeting these demands requires an engineering culture of autonomy and a database platform that scales effortlessly.
Based in Spain, Klikin operates with the agility of a startup despite being a subsidiary of energy multinational Repsol. When Repsol acquired a majority stake in Klikin in 2017, Waylet was a modest application with approximately 40,000 registered users handling around 5,000 payment transactions a day. But the vision was big.
The company’s strategic plan was to create a comprehensive, easy-to-use, package of energy solutions that would incentivize customer loyalty by offering increasingly greater benefits based on the number of services a user has with Repsol.
“Our role was to materialize those changes and make them a reality,” said Bálder Carraté, Principal Software Engineer, Klikin. Waylet, thus evolved from a simple mobile payment tool into a comprehensive ‘super app,’ that allows users to pay for fuel, charging, carwashes, and utility contracts and with each payment earn variable cashback rewards which can be used in future transactions.
This evolution presented a twofold challenge: scale and complexity. Successfully meeting a gap in the market, combined with an attractive cashback incentive—and rewards increasing in line with the number of Repsol services used—meant Waylet’s user base was growing rapidly. It was also experiencing clear seasonal peaks in service station refueling when traffic could double, sometimes even triple. At the start of a long bank holiday weekend, or change of fortnight in summer, queries could surge from a baseline of around 6,000 to 12,000 per second. Meanwhile, a delay of even a few seconds at a payment terminal could lead to queues at service stations and damage the brand’s reputation.
Simultaneously, the data model needed to evolve rapidly. Integrating home energy management meant processing high-volume meter readings and consumption profiles, fundamentally different data types from transactional payments. Klikin needed a database architecture that could support this exponential growth and diverse feature set without forcing its engineering team to become full-time database administrators.
To secure this flexibility and effortless scale, Klikin built its future on MongoDB Atlas.


