Case Study: Landoop achieves rapid, scalable real-time IoT streaming and analytics with InfluxData's InfluxDB

Landoop - Customer Case Study

Landoop, creator of the Lenses streaming Data Management Platform, set out to solve the challenge of building end-to-end pipelines for massive IoT data flows. Teams needed a way to ingest, process and visualize high‑volume, timestamped device data in real time without deep Kafka or JVM expertise, and they required a scalable time‑series store to persist streaming analytics.

Landoop combined the Kafka ecosystem (Connect, Streams and Lenses SQL) with InfluxDB as the scalable time‑series backend—its InfluxDB sink is the most used connector in Lenses—to deliver fast, SQL-driven stream processing, connector-based ingestion (MQTT) and interactive topology visualizations. The result: deployable IoT pipelines in minutes, real‑time insights for customers across utilities, retail and more, and faster time‑to‑value with enterprise-grade monitoring, scaling and integration.

Landoop

Stefan Bocutiu

Head of Data Engineering