THEIR CHALLENGE
Securing sensitive data at a global scale
Award-winning data security platform, Sentra, is trusted by large enterprises across the US, Europe, and Asia that handle hundreds of petabytes of data across global cloud, SaaS, and on-premises systems. Sentra helps its customers manage this sprawl by scanning data, classifying what is sensitive, and mapping who can view it—ultimately reducing risk and preventing unauthorized access. “The core of Sentra is to classify sensitive data, understand the context of data, and help the customer take actions on that,” says Roy Levine, VP of Research & Development, Sentra.
What sets Sentra apart is its approach. All data processing happens inside the customer’s environment, so sensitive information never leaves their control. The platform’s algorithms are engineered for speed and efficiency, enabling the platform to handle large scale data. And Sentra’s classification accuracy consistently outperforms competitors, making it the obvious choice for enterprises that want to be confident that they have full visibility and control of sensitive and regulated data.
But scale brings challenges. As adoption accelerated, Sentra sought to replace Postgres with a flexible schema that could deliver top speeds at massive data volumes.
To support the world’s largest enterprises and fuel its own rapid growth, Sentra needed a more flexible, scalable foundation. That led the company to MongoDB, setting the stage for faster performance, greater agility, and the next phase of innovation.

