Case Study: Curve achieves real-time, event-driven payments and rapid innovation with Confluent

Curve Opens Up a World of Payment Options with Real-Time, Event-Driven Data Transactions

Curve, a London-based fintech, was growing beyond its original monolithic architecture and self‑managed RabbitMQ setup, which created a single point of failure, slow batch ETL to BigQuery, and frequent maintenance overhead that hindered innovation. To move to real‑time, event‑driven data transactions and unlock new product capabilities, Curve partnered with Confluent and adopted Confluent Cloud’s data‑streaming platform (Kafka), connectors, and Schema Registry.

Confluent implemented a fully managed streaming stack—dedicated Confluent Cloud clusters on a private network, PostgresCdcSource and Kinesis connectors, Schema Registry, and BigQuery/Lambda/S3 sinks—which enabled near‑real‑time data access and immutable event logs. The result: Curve eliminated scalability and maintenance pain, reduced development time through automatic BigQuery table/schema handling, improved data accuracy and consumer security, gained the ability to replay events, and scaled storage on demand, accelerating product delivery and data‑driven insights.

Curve

Gustavo Ferreira

Tech Lead Software Engineer