What is the main difference between InfluxDB and TDengine?

InfluxDB and TDengine are both time series databases but differ in their approach, features, and target audience. Compare their GitHub stats, technology stack, and community adoption to make the best choice.

Which is better: InfluxDB or TDengine?

The choice between InfluxDB and TDengine depends on your specific needs, technical requirements, and team preferences. Both are quality open source solutions with active communities.

Can I migrate from InfluxDB to TDengine?

Migration between InfluxDB and TDengine is possible but requires careful planning. Consider data export/import capabilities, feature parity, and potential workflow changes.

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InfluxDB vs TDengine

Learn how InfluxDB and TDengine differ in their key features, development activity, technology stack and community adoption, so you can decide which of these time series databases is best for you.

InfluxDB

InfluxDB handles high-velocity, high-resolution time series data at scale, built for telemetry, edge devices, IoT, and physical AI workloads.

Visit InfluxDB

TDengine

High-performance time-series database with industrial data management, built-in stream analytics, and AI-driven anomaly detection for operational environments.

Visit TDengine

Detailed Comparison

Both InfluxDB and TDengine have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, activity, technology, maturity, licensing and features when making your decision.

Comparable

Community & Popularity

Both tools have similar popularity levels, with InfluxDB having 31,678 stars and TDengine having 25,021 stars on GitHub. In terms of developer contributions, TDengine has 5,013 forks, indicating strong developer engagement.

Comparable

Development Activity

Both projects show recent activity, with InfluxDB last updated 15 hours ago and TDengine 1 day ago.

Comparable

Technology Stack

Both tools share common technology foundations, being built with Bash, Python, Rust. However, they differ in their additional technology choices: TDengine leverages JavaScript, CSS, Golang, C, Objective-C, PHP, Java, C++, MATLAB, C#, Lua, R, Ada.

InfluxDB wins

Project Maturity

InfluxDB has been in development longer, starting 13 years ago, compared to TDengine which began 7 years ago. This 5.9-year head start suggests InfluxDB may have more mature features and established processes.

Comparable

Licensing

The projects use different licenses: InfluxDB is licensed under Apache-2.0 while TDengine uses AGPL-3.0. Consider the licensing requirements when choosing for your project.

Comparable

Use Cases & Features

Both tools serve similar use cases in Time Series Databases.

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InfluxDB vs TDengine: A Detailed Comparison of Time Series Databases in 2026

InfluxDB vs TDengine

Learn how InfluxDB and TDengine differ in their key features, development activity, technology stack and community adoption, so you can decide which of these time series databases is best for you.

InfluxDB

InfluxDB handles high-velocity, high-resolution time series data at scale, built for telemetry, edge devices, IoT, and physical AI workloads.

Visit InfluxDB

TDengine

High-performance time-series database with industrial data management, built-in stream analytics, and AI-driven anomaly detection for operational environments.

Visit TDengine

Detailed Comparison

Both InfluxDB and TDengine have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, activity, technology, maturity, licensing and features when making your decision.

Comparable

Community & Popularity

Comparable

Development Activity

Both projects show recent activity, with InfluxDB last updated 15 hours ago and TDengine 1 day ago.

Comparable

Technology Stack

InfluxDB wins

Project Maturity

Comparable

Licensing

The projects use different licenses: InfluxDB is licensed under Apache-2.0 while TDengine uses AGPL-3.0. Consider the licensing requirements when choosing for your project.

Comparable

Use Cases & Features

Both tools serve similar use cases in Time Series Databases.

Other tool comparisons to consider