Usage & Enterprise Capabilities

Best for:Energy & UtilitiesManufacturing (Industry 4.0)Automotive & Connected CarsSmart Cities & InfrastructureIT Ops & Application Monitoring
TDengine is an open-source, purpose-built time-series database designed for the massive data volumes and high-speed requirements of the Internet of Things (IoT). Unlike general-purpose time-series databases, TDengine provides an all-in-one solution that includes caching, stream processing, and event-driven data handling, significantly reducing the complexity of IoT architectures.
It is engineered to handle massive numbers of data sources (meters, sensors, or devices) and provides a unique "one-table-per-device" modeling approach that ensures high-speed ingestion and instant querying even under heavy load. By collapsing multiple layers of the typical IoT backend into a single system, TDengine helps organizations lower their total cost of ownership and accelerate deployment.
Self-hosting TDengine gives industrial and infrastructure teams the performance and reliability needed for mission-critical monitoring while keeping sensitive operational data local and secure.

Key Benefits

  • Extreme Throughput: Ingest millions of items per second on a single instance.
  • Simplified Stack: Replace Redis, Kafka, and the database with one TDengine cluster.
  • Cost Efficient: Drastic reduction in cloud storage and CPU costs compared to InfluxDB or Timescale.
  • Developer Friendly: Use standard SQL for everything—no complex new query languages to learn.
  • Cloud-Native Resilience: Built to run on Kubernetes with automated failover and scaling.

Production Architecture Overview

A production TDengine (v3.0+) cluster consists of:
  • dnodes (Data Nodes): Handle data storage, query processing, and management.
  • mnodes (Management Nodes): Manage cluster metadata and node status (distributed).
  • qnodes (Query Nodes): Dedicated compute resources for complex aggregations.
  • Load Balancer: Standard TCP/HTTP load balancer to distribute client requests.
  • Persistent Storage: Local high-speed NVMe/SSD for hot data and HDD/S3 for archival.

Implementation Blueprint

Implementation Blueprint

Prerequisites

sudo apt update && sudo apt upgrade -y
sudo apt install docker.io docker-compose -y
sudo systemctl enable docker
sudo systemctl start docker
shell

Docker Compose Production Setup (Standalone Instance)

Ideal for edge deployments or smaller industrial monitoring setups.
version: '3'

services:
  tdengine:
    image: tdengine/tdengine:latest
    container_name: tdengine
    ports:
      - "6030:6030"
      - "6041:6041"
    volumes:
      - tdengine_data:/var/lib/taos
      - tdengine_log:/var/log/taos
    environment:
      - TAOS_FQDN=tdengine
    restart: always

volumes:
  tdengine_data:
  tdengine_log:

Kubernetes Production Deployment (Recommended)

Deploy using the official TDengine Helm chart for high-availability clusters.
helm repo add tdengine https://helm.tdengine.com
helm install tdengine tdengine/tdengine --namespace iot-system --create-namespace
Benefits:
  • StatefulSet Management: Guarantees pod identity and stable storage for dnodes.
  • Automatic Scaling: Increase dnode replicas as your device count grows.
  • Persistent Volume Claims: Automatically attach high-speed cloud storage to your database nodes.

Scaling Strategy

  • Increase vnodes: Adjust the number of virtual nodes (vnodes) per dnode to maximize CPU utilization.
  • Separate Management Nodes: In large clusters, run mnodes on dedicated, isolated pods.
  • Tiered Storage: Use TDengine's tiered storage configuration to move data older than 30 days to S3-compatible object storage.

Reliability & Monitoring

  • Raft Redundancy: Configure at least three replicas for critical data to ensure continuous operation during node failure.
  • Grafana Integration: Use the official TDengine Grafana plugin for real-time operational dashboards.
  • Backup Tool: Use taosdump for full and incremental logical backups of individual databases or the entire cluster.

Recommended Hosting for TDengine

For systems like TDengine, we recommend high-performance VPS hosting. Hostinger offers dedicated setups for open-source tools with one-click installer scripts and 24/7 priority support.

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