TimechoDB review
A self-hosted industrial IoT database with SQL, native APIs, MQTT, and OPC UA.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
TimechoDB is an enterprise time-series database for industrial and IoT workloads. It supports time-series storage and querying, SQL access for table-model data, configurable device-level TTL retention rules, and deployment across standalone, distributed cluster, dual-active, and Docker models. Its focus suits teams managing device, edge, and industrial data that need multiple ingestion paths and control over deployment. Linux and API access are supported, with Docker and Docker Compose options for containerized environments.
Pricing follows a contact-sales model, making TimechoDB a fit for organizations that prefer vendor-led evaluation, enterprise support, or customization. The product is self-hosted, so buyers should account for the operational responsibility that comes with managing infrastructure and deployments. Distributed clusters use ConfigNodes and DataNodes, and capacity can be expanded by adding DataNodes. These capabilities make the product relevant to teams planning growth beyond a single database instance, while buyers seeking a fully managed service or transparent plan comparison should consider alternatives built around those requirements.
TimechoDB’s strongest differentiator is its industrial connectivity. Native client APIs cover Java, Python, C, C++, Go, C#, Node.js, and Rust, while JDBC and ODBC support SQL-oriented access. MQTT ingestion includes a built-in broker integration, and OPC UA supports protocol integration and data push; OPC DA and REST API are also available. This breadth fits mixed industrial environments with existing devices, applications, and operational systems. Choose TimechoDB when self-hosting, protocol coverage, SQL, and cluster expansion matter together. Choose another product if you need published tier pricing, managed hosting, or a narrowly focused database with fewer deployment responsibilities.
TimechoDB pros and cons
- Where it wins
- Native APIs for Java, Python, C, C++, Go, C#, Node.js, and Rust
- MQTT, OPC UA, OPC DA, JDBC, ODBC, and REST API connectivity
- Distributed clusters with device-level TTL retention rules
- Where it doesn't
- Self-hosted deployment requires infrastructure management
- Pricing uses a contact-sales model
- AI capability is listed without specific features described
TimechoDB fact sheet, pricing and score →
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