Industrial Internet


Break down the data silos of the past and enter the digital age with a storage system that enables high utilization and efficiency

TDengine Solution

Background

The sensors in modern industrial facilities constantly generate huge volumes of timestamped data – a perfect use case for a time-series database. This data is mainly collected or aggregated by monitoring, inspection, and analysis devices in the fields of manufacturing, energy, chemical, and construction. The size of these data sets is extremely large, and they are written to often but read infrequently.

Requirements and Pain Points

The main issues with traditional solutions are as follows:

  • Low write throughput: Single-node systems are not able to provide the throughput necessary to write hundreds of millions of time-series data points.
  • High storage costs: Traditional solutions cannot effectively compress time-series data, causing increased data storage requirements.
  • High maintenance: Single-node systems require specialized database administrators to split tables and databases.
  • Poor query performance: Traditional systems do not perform well when aggregating and analyzing massive data sets.

The requirements for industrial customers are as follows:

  • Feature stability
  • High-performance data writes
  • High-performance queries, including querying new and historical data
  • Option to deploy in the cloud
  • Option to deploy on-premises
  • Horizontal scalability
  • High availability
  • Connection with big data platforms in a convenient manner

Solution Architecture

Benefits

  • High performance: millions of concurrent writes, tens of thousands of concurrent reads, and the ability to handle a large number of aggregate queries without performance deterioration
  • High availability: cluster deployment, horizontal scaling, and no single points of failure provide a stable foundation for production environments
  • Reduced cost: low requirements on hardware resources and high compression ratio reduce hardware costs by 70%
  • High level of integration: message queue, stream processing, and caching features included with the database as a single solution
  • Easy to learn: familiar interface, SQL support, and no-code complex queries make it easy for relevant personnel to interact with the system

Industrial Internet Case Studies

Industry needs end-to-end, interoperating solutions that bridge the gap between equipment and the Internet. See how Siemens used time-series technology to build such a solution.
by
Hualie Shen (GDAES)
Hualie Shen (GDAES)
GESRI built a highly scalable and performant environmental monitoring and data governance system for real-time detection and early warning of anomalies in pollution discharge based on stringent government requirements.
TDengine, with its small compute and storage footprint, and therefore low energy costs, is the natural choice for an energy conservation and management platform for Industry 4.0.
TDengine serves as a solution for monitoring in the HeyGears 3D pringting system. The problems we’ve encountered in Hadoop system can be easily solved with its simple SQL-like syntax.