SNCF

SNCF keeps trains running with petabytes of data on Scality RING

sncf case study

France’s national railway company entrusts Scality with its mission-critical data

Founded in 1938, France’s national state-owned railway company, Société Nationale des Chemins de fer Français (SNCF), operates the country's national rail traffic along with Monaco, including the TGV, on France's high-speed rail network. Its functions include operation of railway services for passengers and freight, as well as maintenance and signalling of rail infrastructure. The railway network consists of about 35,000 kilometers (22,000 mi) of route, and about 14,000 trains are operated daily.

SNCF Réseau’s LiDAR project uses cutting-edge data collection technology and techniques, including video capture from train-attached cameras and drones, 3D images of railways, and terrain and data collection from IoT-connected switches and signals. This data is used to develop simulations and make predictions that keep SNCF’s grid and equipment working for passengers and freight.

The challenge

The primary challenge was storing very large volumes of data above several petabytes (and continuously growing). SNCF needed a technological solution that allowed them to flexibly manage the storage of this data in a scalable, secure way.

The outcome

SNCF chose Scality RING to store their mission-critical data on HPE storage servers because it meets their high standards for:

  • Quick access to data for users
  • Scalability without limits
  • Cost-effectiveness
  • Easy management
  • Responsive support

As the foundation of SNCF’s data storage solution, Scality RING is used for railroad track analysis, including storage of drone images and data. SNCF anticipates an explosion of data growth with storage needs that grow as they do. Now they have a solution that can keep up—and keep their operations running smoothly.

  • “The advantage of Scality, in addition to its proximity, is its ability to innovate, as well as the quality and robustness of its technology.”

    Bruno Landes Head of Earthworks and Topography Division, SNCF

Use Cases

  • Accelerate data insights. Boost performance. Zero downtime.

    Big data storage

    Read More