TDengine is a high-performance time-series database designed for Industrial IoT, enabling real-time ingestion, storage, and analysis of large datasets generated by billions of sensors. It addresses the challenges of managing high-frequency data and provides efficient data compression and zero-code integration with various industrial data sources, facilitating operational efficiency and predictive maintenance.
Funding
$67M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Managing high-frequency data from billions of sensors in Industrial IoT environments presents challenges in real-time ingestion, efficient storage, and effective analysis. Traditional database solutions often struggle with the scale and velocity of this data, leading to performance bottlenecks and increased costs.
Solution
TDengine is a high-performance, scalable time-series database (TSDB) designed specifically for Industrial IoT. It addresses the challenges of ingesting, storing, and analyzing massive datasets generated by industrial sensors and data collectors. TDengine offers features such as efficient data compression, tiered storage, and built-in connectors for various industrial data sources, enabling real-time insights for applications like predictive maintenance, condition monitoring, and operational efficiency. The database provides a comprehensive solution for industrial data, including data subscription, caching, and stream processing, accessible through standard SQL.
Target Audience
TDengine targets organizations in industries such as renewable energy, manufacturing, and connected cars that require a high-performance time-series database for managing and analyzing large volumes of industrial IoT data.
Features
- Distributed scalable architecture for high-performance ingestion and querying of time-series data
- Efficient data storage with tiered storage options and high data compression ratios (up to 10:1)
- Built-in connectors for industrial data sources like MQTT, Kafka, OPC, and PI System for zero-code data ingestion
- Comprehensive solution with data subscription, caching, and stream processing capabilities
- Support for standard SQL for data interaction
- Client libraries available for various programming languages, including C#, Go, Node.js, and Python
- Support for both on-premises deployment (TDengine Enterprise) and a fully managed cloud service (TDengine Cloud)
- Support for data subscription with interfaces for data consumption and offset management