Case Study: DynoSense achieves scalable, real-time health‑scanner analytics with DataStax

DynoSense Advances Health Scanner Analytics with DataStax

DynoSense is a medical-technology startup whose Dyno™ scanner captures more than 23 health metrics (ECG, SpO2, respiration, temperature, non‑cuff blood pressure, etc.) in under a minute. Their challenge was reliably storing and processing high‑velocity sensor data in the cloud and running real‑time analytics for tasks like denoising and chronic‑disease detection.

They adopted Apache Cassandra via DataStax Enterprise for its easy horizontal scalability, familiar CQL, and developer tools (DevCenter, OpsCenter), and used DSE Analytics with Spark to parallelize real‑time jobs. The result: simplified scaling (add a node with a single command), faster analytics performance, reduced setup time, and strong startup support and documentation that sped deployment and development.

DynoSense

Robin Chan

Director of Software Engineering