Leverage Azure Cosmos DB for time-series for IoT Apps
summary
Claims that Cosmos DB serves as a single IoT datastore for devices, metadata, alarms and time-series telemetry and demonstrates a working pipeline: Azure IoT Hub → Function → Cosmos DB with a simulator sending five devices at scale (10,000 messages per device) and writes showing low-RU, low-latency inserts. Uses partition key = deviceId or deviceId_month (composite recommended), autoscale RUs, change feed to push older data to cold storage, and TTL (1 year) to keep a hot store while archival to Data Lake works.
AI-written summary · about
chapters (10)
- 0:00Introduction
- 1:37What is timeseries
- 4:13Cosmos DB introduction
- 6:03IoT reference architecture
- 11:30IoT data entities
- 13:24Timeseries requirements
- 15:52Partitioning
- 17:45Request Unit
- 20:10Demo
- 24:57Key takeaways
related talks
10mBuilding IoT Apps with JSONB & Timeseries
01h 03mTime Traveling in the Cloud
27mIntegrating Azure Cosmos DB with the Azure Ecosystem
45mGetting the Most from NoSQL in the Cloud with Azure Cosmos DB
49mData management and Analytics for Industrial IOT
57mSensors, data and dashboards: Azure IoT end-to-end
01mCustomer Story: Empowering Health Research with Azure Cosmos DB
14mPower real-time data streams from anywhere to Cosmos DB with Confluent