Learn how QuestDB 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.
Last 30 days
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Repository age
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Last 30 days
Last commit
Repository age
Version
License
Repository

Both QuestDB and TDengine have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Both tools have similar popularity levels, with QuestDB having 17,268 stars and TDengine having 25,068 stars on GitHub. In terms of developer contributions, TDengine has 5,017 forks, indicating strong developer engagement.
QuestDB and TDengine are moving at much the same rate, adding 80 stars and adding 100 stars respectively over the last 30 days (+0.5% vs +0.4%). Neither is pulling away from the other on momentum alone.
Both projects show recent activity, with QuestDB last updated 11 hours ago and TDengine 5 days ago.
Both tools share common technology foundations, being built with JavaScript, Bash, Python, Golang, C, Rust, Objective-C, PHP, Java, C++, C#. However, they differ in their additional technology choices: TDengine leverages CSS, MATLAB, Lua, R, Ada.
QuestDB has been in development longer, starting 12 years ago, compared to TDengine which began 7 years ago. This 5.3-year head start suggests QuestDB may have more mature features and established processes.
The projects use different licenses: QuestDB is licensed under Apache-2.0 while TDengine uses AGPL-3.0. Consider the licensing requirements when choosing for your project.
Both tools serve similar use cases in Time Series Databases.