TDengine
Database designed to process time series data
TDengine is an open-source, high-performance, distributed time series database that is designed to handle massive amounts of time series data. It was developed by Taos Data, a China-based data analytics company, and is known for its high speed, low latency, and scalability. One of the key features of TDengine is its ability to handle high-speed data ingestion at a very low cost. It uses a columnar database structure to store time series data, which allows for fast retrieval and analysis. TDengine also supports distributed architecture, which enables the system to scale horizontally across multiple nodes and provides a fault-tolerant and highly available system. TDengine has a range of features and tools that make it an attractive option for organizations that need to store and analyze large amounts of time series data. It has a variety of data processing functions and supports complex data analysis, machine learning, and data visualization. The platform also includes tools for data backup and restoration, as well as data security and access control. TDengine supports a wide range of programming languages, including C/C++, Python, and Java, which makes it easy for developers to integrate it into their existing workflows. Additionally, it provides a comprehensive set of APIs for different programming languages, which allows developers to build their own applications on top of the TDengine database. Overall, TDengine is a powerful and flexible database system that is well-suited for handling large volumes of time series data. Its open-source nature and community-driven development make it an attractive option for organizations looking for a scalable and reliable solution for managing time series data.