Apache IoTDB vs openGemini

Apache IoTDB is an open-source industrial IoT time-series database for collecting, storing, managing, and analyzing device data across edge and cloud deployments. The project describes high-speed writes for millions of networked devices alongside fast reads. Query features include aligning time across devices and sensors, time-series computation, and aggregation by time dimensions. Ingestion options include IoTDB-SQL, JDBC, Java, C++, Python, and Go native APIs, REST, MQTT, CSV, and TsFile. Named analysis ecosystem examples include Hadoop, Spark, Flink, and Grafana. Deployment options include cloud installation, a desktop terminal tool, and synchronization between cloud and on-premise machines. The REST service is disabled by default and uses Basic Authentication except for the health check endpoint. Data and cluster permissions can be managed through users, roles, and privileges. The homepage states disk storage can cost less than $0.23 per GB. The project lists energy, aerospace, transportation, steel, and other IoT scenarios. Its JDBC documentation cautions that insert operations may not provide high-performance writing and recommends the Java Native API for Java applications.

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.