openGemini vs QuestDB

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.

QuestDB is a time-series database for environments where low latency matters, including mission-critical workloads. It supports standard SQL through a vectorized execution engine, along with time-series extensions such as SAMPLE BY, ASOF, and HORIZON JOIN. QuestDB advertises ingestion speeds of 8M+ rows per second. The Open Source edition is self-managed and available as binaries, containers, or source code; it is single-instance and supports Parquet storage and PostgreSQL Wire Protocol compatibility. Ingestion options include QuestDB Wire Protocol, InfluxDB Line Protocol, REST API, native client libraries, SQL INSERT, Kafka connector, and CSV import. Listed integrations include Grafana, Power BI, Apache Kafka, Telegraf, Redpanda, Apache Flink, Pandas, and Apache Spark. Open Source costs nothing and includes community support. Enterprise adds security controls, replication, automatic failover, object-storage tables, and dedicated support with response-time SLAs.