
TDengine
8.3#1 in time-series databasesFree planFree planWebAPILinuxmacOS
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| Fact | TDengine | Warp 10 |
|---|---|---|
| Deployment | Self-hosted deployments can run at the edge, in containers or virtual machines, on local servers, or in public, private, or hybrid clouds. | Warp 10 is available in Standalone, Standalone+, and Distributed versions; the versions differ mainly in how the storage engine is implemented. |
| Headquarters | San Jose, California, United States | 29490 Guipavas, France |
| Installation | Official packages support Linux and Windows, and documentation also provides Docker and Kubernetes deployment paths. | The download page describes binary installation on your own infrastructure and a Docker image that includes Warp 10, WarpStudio, and Sensision. |
| Integrations | The documented ecosystem includes Grafana integration, Kafka integration, MQTT, OPC, PI System and Excel connectivity. | The platform can fetch data from SQL and NoSQL databases, document stores, other time series databases, and monitoring platforms. |
| Support | Annual licenses include business-hours standard support, while premium support offers 24×7 Severity 1 coverage; free-tier support is optional at $3,375 per year. | Warp 10 documentation directs users to its community Slack to report issues or missing documentation. |
TDengine is designed for industrial enterprises and organizations running traditional data historians or legacy industrial IoT platforms, especially those needing time-series ingestion and analysis.
Warp 10 may suit teams collecting and analyzing time series or sensor data that want self-hosted or distributed deployment options. Its documented integrations can be useful to teams working with notebooks, processing frameworks, databases, or dashboard tools.