Open‑Source, High‑Performance Simplified Solution for Time Series Data

TDengine™ is an open-source, cloud-native time series database (TSDB) optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. It enables efficient, real-time ingestion, processing, and monitoring of petabytes of data per day, generated by billions of sensors and data collectors.

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High Performance

TDengine is the only time series database that solves the high-cardinality issue, supporting billions of data collection points while outperforming other time series databases in data ingestion, querying and compression.


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Simplified Solution

Through built-in caching, stream processing, and data subscription features, TDengine provides a simplified solution for time series data processing that significantly reduces system design complexity and operational costs.


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Cloud Native

Through native distributed design, sharding and partitioning, separation of compute and storage, Raft, support for Kubernetes deployment, and full observability, TDengine can be deployed on public, private or hybrid clouds.


Trusted by Developers from Startups to Giants

Over 200k Installations and 20k GitHub Stars

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Connected Cars:
DJI Automotive processes autonomous driving data in milliseconds

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Connected Cars:
Li Auto reduces IoT data storage and compute nodes from 17 to only 5

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Industrial Internet:
Siemens SIMICAS® solution simplifies industrial data workflows

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Internet of Things:
OPPO lowers storage resources for IoT product data by 75%

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Industrial Internet:
TCL builds an energy conservation and management platform for Industry 4.0

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RCT Power builds a platform for its residential energy storage system

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Why Developers Choose TDengine

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Open Source

The core components of TDengine, including clustering, are all available under open-source licenses. It has an active developer community with 18k stars on GitHub and over 100k running instances worldwide.


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Ease of Use

TDengine significantly reduces the effort to deploy and maintain a time series database. It provides a simple interface and seamless integrations for third-party tools, giving users and developers easy access to data.


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Easy Data Analytics

Through supertables, storage and compute separation, data partitioning by time interval, pre-computation, and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way. 


Learn more about TDengine

Why Decision Makers Choose TDengine

Reduce Time Series Data Processing TCO by 50% or More

Compared with other time-series data solutions, TDengine reduces TCO in four ways:

  • Reduces hardware costs with higher performance
  • Reduces learning costs with standard SQL support and easy integration with third-party tools
  • Reduces system complexity and operating costs with a simplified, fully integrated solution
  • Reduces overhead and overprovisioning costs with flexible pricing options

Learn more about how TDengine reduces costs

Time Series Database Usage Scenarios

Smart hardware, connected equipment, smart homes, smart cities, smart water

Smart manufacturing, process industry, production digitization, digital twin

IDC, host, virtual machine, network device, container, micro service monitoring

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TBox data, battery management system, autonomous driving, fleet management

Clean energy, power distribution, smart meters, energy management

Stock, securities and crypto market data

Learn more about time series databases

Selected Blogs

Sean Ely
Sean Ely
This document contains the release notes for TDengine
TSBS test results show that TDengine offers significant advantages over InfluxDB and TimescaleDB in data ingestion, compression, and query performance.
Shengliang Guan
Shengliang Guan
Schemaless writing automatically creates storage structures for your data as it is being written to TDengine, so that you do not need to create supertables in advance.
The CHIPS Act is a crucial milestone in the renaissance of manufacturing in the United States. But are we ready for it?
TDengine Team
TDengine is delighted to announce today that it has joined NVIDIA Inception as a community member.
Shengliang Guan
Shengliang Guan
TDengine uses various kinds of caching techniques to efficiently write and query data. This article describes the caching component of TDengine.

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