kdb+ vs openGemini
kdb+
kx.com
openGemini
opengemini.orgSide by side
| Figure | kdb+ | openGemini |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Time-Series Databases | 7.9 (#19) | 8.5 (#8) |
| Security | kdb+ can use SSL/TLS to encrypt connections with OpenSSL, configured with certificates and keys. | Username and password authentication is supported but disabled by default in the configuration; HTTPS also requires configuration to enable. |
| Use cases | KX describes kdb+ use in trading, fraud detection, and IoT monitoring, and identifies Capital Markets, Defense, and High-Tech Manufacturing as served sectors. | The project describes monitoring and observability, IoT, and operations data analysis as typical application scenarios. |
| What it does | kdb+ is a time-series database and analytics engine powered by the q vector language, built to capture, analyze, and act on real-time and historical data. | openGemini is an open-source, cloud-native distributed time-series database for storing and analyzing massive time-series data. |
Plans
In their own words
kdb+
kdb+ is a time-series database and analytics engine from KX, built around the q vector language. It captures and analyzes real-time and historical data for time-sensitive workloads. KX describes in-memory ingestion and analysis with sub-millisecond performance. Its storage layout separates newest in-memory records in an RDB, recent disk data in an IDB, and long-term columnar archives in an HDB. Query options include q and q-SQL, with support for Python, Java, C#, C++, Rust, R, and open-source libraries. Data can arrive through tickerplants, feed handlers, batch mode, TCP/IP, Apache Kafka, or supported programming languages. KX describes applications in trading, fraud detection, and IoT monitoring across Capital Markets, Defense, and High-Tech Manufacturing. Deployments cover Linux, macOS, Windows, APIs, and self-hosted environments, with cloud documentation for AWS, Google Cloud Platform, and Microsoft Azure. SSL/TLS connections use OpenSSL certificates and keys.
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.