openGemini vs Warp 10
openGemini
opengemini.org
Warp 10
warp10.ioSide by side
| Figure | openGemini | Warp 10 |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Time-Series Databases | 8.5 (#8) | 8.1 (#16) |
| Deployment | The installation guide describes Linux, macOS, and Windows support; it recommends macOS and Windows for development and debugging. | Warp 10 is available in Standalone, Standalone+, and Distributed versions; the versions differ mainly in how the storage engine is implemented. |
| Purpose | openGemini is an open-source, cloud-native distributed time-series database for storing and analyzing large volumes of time-series data. | Warp 10 is a modular open source platform for collecting, storing, and analyzing sensor data. |
| Security | Username and password authentication is supported but disabled by default in the configuration; HTTPS also requires configuration to enable. | Warp 10 uses cryptographic tokens to control access, and its ingress API requires a valid write token in the X-Warp10-Token header. |
Plans
In their own words
openGemini
openGemini is a free, open-source distributed database for storing and analyzing time-series data, including metrics, logs, and traces. Its stated application areas include monitoring and observability, IoT, and operations analysis. The system uses an MPP architecture with ts-sql, ts-meta, and ts-store components that can be scaled independently. Column-based storage, compression, automatic partitioning, and LSM-based techniques are part of its storage design. A built-in AI analysis platform provides real-time anomaly detection. Query options include InfluxQL, PromQL, and GeminiQL; ingestion methods include InfluxDB Line Protocol, Apache Arrow Flight, and Prometheus remote_write. It also provides HTTP APIs for expression and metadata queries and remote reads and writes. Deployment is supported on Linux, macOS, and Windows, as well as through Docker and Kubernetes. Authentication is disabled by default and must be enabled in configuration. PromQL compatibility covers 90% of Prometheus functions and operators, with some unsupported.
Warp 10
Warp 10 is a free, open-source platform for collecting, storing, and analyzing time series and Geo Time Series data, including sensor data. It runs as a server that accepts HTTP requests for ingestion and WarpScript execution, and supports API, Linux, macOS, web, Windows, and self-hosted deployments. The platform is available in Standalone, Standalone+, and Distributed versions whose main difference is storage-engine implementation. Standalone uses LevelDB and is described as suitable for a few tens of millions of time series and a few hundreds of billions of datapoints; larger needs are directed to Distributed, which uses FoundationDB. Warp 10 includes more than 1,300 time-series functions. Installation can use binaries on your infrastructure or a Docker image containing Warp 10, WarpStudio, and Sensision. Integrations include Jupyter, Zeppelin, Spark, Flink, MQTT, BACNet, NodeRed, NiFi, SQL and NoSQL sources, Grafana, and PowerBI. Ingestion supports HTTP POST, WebSocket, UDP, MQTT, and Kafka. Cryptographic READ and WRITE tokens control access, and metadata encryption is enabled by default.