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 TDengineโข, the only time-series database designed for Industrial IoT.
Instances worldwide
GitHub stars
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
Solving Real-World Data Challenges Across Industries
McDonald’s achieves sub-second analytics at scale with TDengine
Siemens simplifies industrial data processing workflows with TDengine
Lotus increases data handling capacity and efficiency to serve car owners worldwide
Extracellular ensures seamless data collection and long-term scalability for bioprocess data
Nevados streamlines data operations for solar trackers with TDengine
SailADV delivers high-performance telemetry and predictive diagnostics for luxury yachts
Mingyang stores billions of data points from 15,000 wind turbines in TDengine
Gotion ingests millions of BESS data records daily at 10:1 compression in TDengine
CATL monitors key predictive maintenance metrics for over 10,000 devices in real time
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 SolutionHigh-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 SolutionCondition 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 SolutionOperational 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 SolutionLatest Updates
TDengine is excited to announce that TDgpt now supports covariate forecasting for time-series data.
TDengine has introduced a Power BI integration, making it easy to bring all your data together.
This article demonstrates how to integrate TDengine with Perspective for real-time stream analytics.
This article describes how to install TDengineโs JDBC connector in Ignition and integrate the two products.
To demonstrate TDengine’s robust performance, we evaluated the platform against the recently released InfluxDB 3 in an IoT scenario.
This article discusses the algorithms included with TDgpt and their use cases along with a usage example.
