KairosDB vs openGemini
KairosDB
kairosdb.github.io
openGemini
opengemini.orgSide by side
| Figure | KairosDB | openGemini |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · Time-Series Databases | 7.3 (#31) | 8.5 (#8) |
| Deployment | The documentation says KairosDB runs under Kubernetes and is mostly stateless, while Cassandra can be harder to run efficiently there. | The installation guide describes Linux, macOS, and Windows support; it recommends macOS and Windows for development and debugging. |
| Purpose | KairosDB is a fast, distributed, scalable time-series database built on Cassandra. | openGemini is an open-source, cloud-native distributed time-series database for storing and analyzing large volumes of time-series data. |
| Security | The KairosDB pages reviewed do not state security certifications or compliance claims. | Username and password authentication is supported but disabled by default in the configuration; HTTPS also requires configuration to enable. |
Plans
In their own words
KairosDB
KairosDB has no write-up on Specifiction yet; its figures are above.
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.