Hi everyone,
I’m currently working on a project involving real-time sensor data collection from multiple IoT devices, and I’m exploring GridDB as the backend due to its time-series capabilities and scalability. I’ve gone through the documentation and successfully installed the Python client. However, I’m running into a few roadblocks with the actual data ingestion and schema modeling.
Here’s a brief overview of my setup:
- Each IoT device sends temperature, humidity, and pressure readings every 10 seconds.
- I would like to store this data in a way that’s efficient for time-based queries, e.g., querying average temperature from device X over the last 30 minutes.
- My goal is also to eventually visualize this data using something like Grafana or a custom dashboard.
Here are some of the questions I’m hoping to get help with:
- What’s the recommended container model for this use case? Should I use a separate time-series container per device, or is there a more efficient structure?
- Is it possible to batch insert records from multiple devices in one transaction, or should I handle each insert separately?
- How should I structure the timestamp field? Should I explicitly set it, or can GridDB auto-generate it reliably?
- Any tips or caveats when using the Python client for bulk inserts or querying large datasets?
If anyone has worked on similar applications or has suggestions—especially in the context of a power bi course in kolkata—I’d really appreciate your insights. Code snippets or references to relevant examples would also be incredibly helpful.
Thanks in advance!