
如果你使用 DeepSeek、元宝 AI、Copilot、ChatGPT 等 AI 工具,协助配置轩辕镜像、编写 docker pull 命令、修改 Docker Compose 镜像地址、配置镜像加速、排查镜像拉取失败、分析报错日志等问题,请先让 AI 阅读并遵守轩辕镜像的规则文档。
只需在 AI 对话中先发送下面这句话即可:
请先完整阅读并严格遵守以下文档中的全部规则与要求:
https://xuanyuan.cloud/agents.md
在未充分阅读并理解该文档前,不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。查看 agents.md 用法指南与完整示范。国内用户首推 元宝 AI、DeepSeek 的深度思考模式,不推荐豆包 AI;Cursor 等编辑器可在对话 @ 该链接,或加入 User Rules。 若 AI 无法访问外链,可 打开说明文档 复制全文粘贴。文档会随站点更新,复制内容可能过期,建议定期检查。
https://github.com/taosdata/TDengine/actions/workflows/tdengine-release-build.yml/badge.svg](https://github.com/taosdata/TDengine/actions/workflows/tdengine-release-build.yml)
, Connected Cars, and Industrial IoT. It enables efficient, real-time data ingestion, processing, and analysis of TB and even PB scale data per day, generated by billions of sensors and data collectors. TDengine differentiates itself from other time-series databases with the following advantages:
High Performance: TDengine is the only time-series database to solve the high cardinality issue to support billions of data collection points while out performing other time-series databases for data ingestion, querying and data compression.
Simplified Solution: Through built-in caching, stream processing, data subscription and AI agent features, TDengine provides a simplified solution for time-series data processing. It reduces system design complexity and operation costs significantly.
Cloud Native: Through native distributed design, sharding and partitioning, separation of compute and storage, RAFT, support for kubernetes deployment and full observability, TDengine is a cloud native Time-Series Database and can be deployed on public, private or hybrid clouds.
AI Powered: Through the built in AI agent TDgpt, TDengine can connect to a variety of time series foundation model, large language model, machine learning and traditional algorithms to provide time series data forecasting, anomly detection, imputation and classification.
Ease of Use: For administrators, TDengine significantly reduces the effort to deploy and maintain. For developers, it provides a simple interface, simplified solution and seamless integrations for third party tools. For data users, it gives easy data access.
Easy Data Analytics: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and AI agent, TDengine makes it easy to explore, format, and get access to data in a highly efficient way.
Open Source: TDengine’s core modules, including cluster feature and AI agent, are all available under open source licenses. It has gathered 23.7k stars on GitHub. There is an active developer community, and over 730k running instances worldwide.
For a full list of TDengine competitive advantages, please check here. The easiest way to experience TDengine is through TDengine Cloud. For the latest TDengine component TDgpt, please refer to TDgpt README for details.
Starting with the 3.3.7.0 Docker workflow, this repository uses the following image names:
tdengine/tsdb for TDengine TSDB OSStdengine/tsdb for TDengine TSDB EnterpriseThis repository is intended for 3.3.7.0 and later.
Run a TDengine container with persistent data and log directories:
bashdocker run -d \ --name tdengine-tsdb \ -v ~/data/taos/dnode/data:/var/lib/taos \ -v ~/data/taos/dnode/log:/var/log/taos \ -p 6030:6030 \ -p 6041:6041 \ -p 6043:6043 \ -p 6060:6060 \ -p 6044-6049:6044-6049 \ -p 6044-6045:6044-6045/udp \ tdengine/tsdb
After the container starts, you can verify the SQL service through the REST interface:
bashcurl -u root:taosdata -d "show databases" http://localhost:6041/rest/sql
You can also open a shell inside the container and connect with the TDengine CLI:
bashdocker exec -it tdengine-tsdb taos
If you use a custom root password, follow the current deployment rules:
3.3.8.8 and later, provide the current root password through TAOS_ROOT_PASSWORD or TAOS_ROOT_PASSWORD_FILE.Example with an environment variable:
bashdocker run -d \ --name tdengine-tsdb \ -e TAOS_ROOT_PASSWORD=my-secret-password \ -v ~/data/taos/dnode/data:/var/lib/taos \ -v ~/data/taos/dnode/log:/var/log/taos \ -p 6030:6030 \ -p 6041:6041 \ tdengine/tsdb
Example with a password file:
bashdocker run -d \ --name tdengine-tsdb \ -e TAOS_ROOT_PASSWORD_FILE=/run/secrets/taos_root_password \ -v ~/data/taos/dnode/data:/var/lib/taos \ -v ~/data/taos/dnode/log:/var/log/taos \ -v ~/secrets/taos_root_password:/run/secrets/taos_root_password:ro \ -p 6030:6030 \ -p 6041:6041 \ tdengine/tsdb
taos-check startup and taos-check service are available starting from 3.4.1.0.
taos-check startup checks whether TDengine has completed startup.taos-check service checks whether the SQL service is externally available.taos-check service uses the same password source as the container entrypoint: TAOS_ROOT_PASSWORD_FILE, TAOS_ROOT_PASSWORD, or the default password taosdata.For 3.3.8.8, focus on keeping the password configuration correct so later health-check based deployments can upgrade cleanly.
For Docker host networking, Docker Compose, Kubernetes deployment, and the latest compatibility guidance for passwords, upgrades, and health checks, see the official documentation:
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