Case Study: Meshify achieves scalable, sub-millisecond IoT sensor ingest and lower infrastructure costs with ScyllaDB

To Prevent Accidents Before They Happen, Meshify Calls on Scylla to Scale IoT Sensor Data

Meshify, an IoT platform for the insurance industry that uses battery-powered sensors to predict and prevent accidents, needed a highly scalable time-series database to handle rapidly growing sensor data. After finding MySQL and managed cloud options unsuitable due to scalability limits, vendor lock-in, data residency and TCO concerns, Meshify selected ScyllaDB (Scylla) to replace their relational backend and meet strict performance and compliance requirements.

ScyllaDB delivered a high-performance, pre-tuned solution that let Meshify run a smaller three-node cluster on i3 instances, spin up nodes in under five minutes, and reduce monitoring and management overhead. The ScyllaDB deployment ingested 23,323,005 data points, sustained 5,000 writes per minute with an insert SLA under 1 ms, and achieved 99th‑percentile read latencies of ~0.7–0.9 ms and write latencies averaging <0.7–1.05 ms, while enabling safe background batching for disaster recovery and lower operational costs.

Meshify

Sam Kenkel

DevOps and Database Reliability Engineer