Case Study: Ceto enhances maritime efficiency with MongoDB Time Series Collections

CETO cuts vessel data storage from 300MB to 3MB per day with MongoDB

Ceto, a maritime logistics company, faced serious scalability and reliability challenges managing high-frequency sensor data from vessel fleets using their previous system. The volume of data—hundreds of megabytes per vessel daily—overwhelmed their infrastructure, risking downtime and hindering their predictive analytics goals. To support its mission of digital transformation, Ceto partnered with MongoDB and adopted MongoDB Atlas with Time Series Collections.

Implementing MongoDB's solution provided robust, scalable data handling with advanced compression. This allowed Ceto to process thousands of data points per second in real-time. The results were substantial: data storage needs dropped from 300MB to just 3MB per vessel daily, and predictive maintenance savings reached approximately $20,500 annually per vessel. MongoDB enabled Ceto to enhance operational efficiency and set the stage for significant future growth.

CETO