Learn how Apache IoTDB 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
Last commit
6 hours agoRepository age
8 yearsVersion
v2.0.11License
Apache-2.0Self-hosted
YesRepository
apache/iotdb
Last 30 days
Last commit
5 days agoRepository age
7 yearsVersion
3.4.3.3License
AGPL-3.0Repository
taosdata/tdengine
Both Apache IoTDB 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.
TDengine significantly outpaces Apache IoTDB in community adoption with 25,172 stars compared to 6,423 stars on GitHub. This 3.9x difference suggests TDengine has a much larger and more active community. In terms of developer contributions, TDengine has 5,014 forks, indicating strong developer engagement.
Apache IoTDB and TDengine are moving at much the same rate, adding 20 stars and adding 27 stars respectively over the last 30 days (+0.3% vs +0.1%). Neither is pulling away from the other on momentum alone.
Both projects show recent activity, with Apache IoTDB last updated 6 hours ago and TDengine 5 days ago.
Both tools share common technology foundations, being built with Bash, Python, C, Objective-C, Java, C++, C#. However, they differ in their additional technology choices: TDengine leverages JavaScript, CSS, Golang, Rust, PHP, MATLAB, Lua, R, Ada.
Both projects started around the same time, with Apache IoTDB beginning 8 years ago and TDengine 7 years ago.
The projects use different licenses: Apache IoTDB 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.
Apache IoTDB provides self-hosting options for complete data control and customization, while TDengine may be primarily cloud-based or require different deployment approaches.