Case Study: Eni achieves faster scientific research and smarter search with MongoDB Atlas

Eni manages terabytes of subsurface data with MongoDB Atlas

Eni, a leading energy company based in Italy, faced the challenge of making vast quantities of unstructured subsurface data actionable for scientific research. Their legacy relational database struggled with the complexity and lack of standardization across different languages and units of measurement, making it difficult to create comprehensive datasets and run queries efficiently. Eni partnered with MongoDB to migrate its document management platform to MongoDB Atlas to better organize, retrieve, and utilize this data.

By implementing MongoDB Atlas and Atlas Charts, Eni created a scalable, cloud-agnostic platform that significantly improved data search and visualization. The solution provided a user-friendly interface for developers and scientists, enabling faster data retrieval and the creation of interactive dashboards without extensive coding. MongoDB reports that this migration drastically reduced development time, delivered significant cost savings, and freed up developers to focus on customization rather than routine maintenance, accelerating innovation across the company.

Eni