High-Performance, Scalable Time-Series Database for Industrial IoT

From predictive maintenance and remote monitoring to AI and ML, the latest industrial applications all have one thing in common — a reliance on large, high quality datasets. And no database better helps you gain real-time insights than TDengine™, the only time-series database designed for Industrial IoT.

700,000

Instances worldwide

23,000

GitHub stars

500+

Global customers

Trusted by 500+ Industrial Customers Worldwide

10x Higher Performance at Any Scale

With its distributed scalable architecture that grows together with your business, TDengine can store and process massive datasets up to 10.6x faster than other TSDBs — all while providing the split-second latency that your real-time visualization and reporting apps demand.

High Performance Distributed Design

90% Reduction of Data Storage Costs

With its unique design and data model, TDengine provides the most cost-effective solution for storing your operations data, including tiered storage, S3, and 10:1 data compression, ensuring that you can get valuable business insights from your data without breaking the bank.

Tiered Storage High Compression

Zero-Code Data Consolidation Across Sites

With built-in connectors for a wide variety of industrial sources — MQTT, Kafka, OPC, PI System, and more — TDengine delivers zero-code data ingestion and extract, transform, and load (ETL) in a centralized platform that acts as a single source of truth for your business.

Data Consolidation Data Sources

Edge–Cloud Synchronization

With automated replication of data between edge and cloud deployments, TDengine ensures cross-site data can be reliably stored without loss or duplication and makes it easy to build distributed systems that combine local responsiveness with centralized insight.

Edge-Cloud Synchronization

AI Agent for Time-Series Analytics

TDgpt is a built-in component of TDengine that provides time-series data forecasting & anomaly detection, supporting AI/ML, including time-series foundation models and large language models, as well as traditional statistical algorithms, all in a single SQL statement.

TDgpt

Modern Solutions for Modern Industrial Applications

Predictive Maintenance

TDengine provides the ideal data backbone for powering IIoT predictive maintenance initiatives to optimize operations, reduce downtime, and enhance decision-making across industries like process manufacturing, renewable energy, and oil & gas.

Our Solution

High-Frequency Data

TDengine efficiently handles high-frequency data ingestion, compresses data to reduce storage costs, and enables fast querying for real-time monitoring and analysis in industrial applications.

Our Solution

Condition Monitoring

With its high ingestion rate, efficient storage, real-time processing capabilities, seamless scalability, and integrated solutions, TDengine is the ideal choice for condition monitoring in any industrial setting.

Our Solution

Operational Efficiency

With its high ingestion rate, efficient storage, real-time processing capabilities, seamless scalability, and integrated solutions, TDengine is the ideal choice for optimizing operational efficiency across various industries.

Our Solution

Latest Updates

To assess the performance of TDengine OSS, a performance evaluation was conducted based on the Time Series Benchmark Suite.

Compare InfluxDB, TDengine, TimescaleDB, and others. Learn how to choose the right time-series database for your use case.

by Joel Brass
July 18, 2025

TDengine offers seamless integration with PostgreSQL, enabling efficient migration of historical data as well as real-time synchronization.

by Joel Brass
July 15, 2025

TDengine can efficiently read data from MySQL and write it into TDengine, enabling migration of historical data as well as synchronization of real-time data.

This article compares relational database management systems with time-series databases.

by Jim Fan
July 14, 2025

Integrating TDengine with ThingsBoard enables seamless data collection, storage, analysis, and visualization for industrial IoT scenarios.