Case Study: CrowdSec achieves real-time AI-driven threat detection and faster growth with MongoDB

CrowdSec ingests 900 million documents every 30 days with MongoDB

CrowdSec, a cybersecurity startup, initially used PostgreSQL for its data storage but faced challenges with developer velocity and agility. The relational database required cumbersome manual migrations for schema changes and caused significant downtime during upgrades, hindering their ability to iterate quickly. Seeking a more agile solution, CrowdSec turned to vendor MongoDB and its product MongoDB Atlas.

By implementing MongoDB Atlas, along with Atlas Search, Vector Search, and Time Series collections, CrowdSec optimized its data management. The solution enabled fast, flexible querying and deep pattern analysis for its threat intelligence data, all without causing operational downtime. As a result, MongoDB significantly accelerated CrowdSec's business growth, allowing it to rapidly enrich its data and deliver one of the best cyber threat intelligence offerings on the market.

CrowdSec