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TDengine™ is a time-series database purpose-built for Industry 4.0 and IIoT.
Our mission is to democratize industrial data systems and make big data accessible, valuable, and affordable for everyone.
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On Premises
TDengine Enterprise
Deploy TDengine on the edge, on a local server, or in a public, private, or hybrid cloud
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TDengine Cloud
Run your industrial data workflows in our fully managed cloud service
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What We Do
TDengine is designed to help traditional industries achieve digital transformation and improve operational efficiency.
TDengine centralizes, stores, analyzes, and shares massive amounts of industrial data so you can scale your operations for Industry 4.0.
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Why Developers Choose Us
* High Performance: outperforms other time-series databases in ingestion, querying, and compression.
* Cloud Native: enables scalability, elasticity, resiliency, observability, and automation in a distributed architecture.
* Ease of Use: reduces effort to deploy your time-series database, with simple, standardized interfaces and seamless integration.
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TDengine OSS
Explore our open source time series database project
# Time-Series Database: Cost-Effective Solution for Modernizing Data Operations in Manufacturing
Jim Fan
January 9, 2025
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The manufacturing industry is experiencing a data-driven revolution. As Industry 4.0 and smart factory technologies reshape operations, manufacturers face the challenge of managing vast streams of time-stamped data from machines, sensors, and processes. Traditional data historians and general-purpose databases are ill-equipped to meet these demands, often resulting in inefficiencies, high costs, and missed opportunities. Enter time-series databases — purpose-built solutions designed to handle the complexities of modern manufacturing data.
## The Problem with Legacy Systems
Legacy data historians, while historically foundational, fall short in the era of smart factories. Their inability to scale efficiently, combined with high costs and limited integration capabilities, creates barriers for manufacturers striving for real-time insights. High-frequency, time-oriented data streams often overwhelm these systems, leading to delays and inefficiencies in operations like predictive maintenance and quality control.
## The Time-Series Advantage
Time-series databases, such as TDengine, offer a transformative solution by addressing the unique requirements of manufacturing data:
* **Scalability and Cost Efficiency**: Built to handle growing data volumes without the need for costly upgrades, time-series databases use advanced compression algorithms to reduce storage needs while maintaining performance.
* **Real-Time Insights**: These databases process and analyze data in real time, enabling manufacturers to detect anomalies, optimize processes, and make informed decisions without delay.
* **Seamless Integration**: Designed to work with Industrial IoT (IIoT) ecosystems, time-series databases support a wide range of protocols and integrate effortlessly with edge and cloud platforms.
## Applications in Manufacturing
Time-series databases excel in various manufacturing scenarios, including:
* **Predictive Maintenance**: By analyzing historical and real-time data from sensors, manufacturers can anticipate equipment failures and schedule maintenance proactively.
* **Vibration Analysis**: Real-time data analysis helps identify inefficiencies, enhancing productivity and reducing costs.
* **Condition Monitoring**: Continuous tracking of key metrics ensures optimal machine performance, safeguarding product quality and regulatory compliance.
## Why TDengine Stands Out
Among time-series databases, TDengine distinguishes itself as a purpose-built solution for Industry 4.0. With features like high ingestion rates, efficient data compression, and support for diverse industrial protocols, TDengine empowers manufacturers to unlock the full potential of their operations. Its ability to scale effortlessly and integrate seamlessly with IIoT environments makes it the ideal choice for smart factories.
## Conclusion
The future of manufacturing lies in leveraging data to drive efficiency and innovation. By adopting time-series databases, manufacturers can overcome the limitations of legacy systems and embrace the opportunities of a data-driven era. With solutions like TDengine, the path to smarter, more efficient factories is clear.
By choosing TDengine as the foundation of your data infrastructure, you can ensure that your plants run smoothly, securely, and affordably — both now and in the future. If you’d like to learn more about how TDengine can help manufacturers overcome data challenges, fill in your email on the right and download our special report today.
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  Jim Fan
  Jim Fan is the VP of Product at TDengine. With a Master's Degree in Engineering from the University of Michigan and over 12 years of experience in manufacturing and Industrial IoT spaces, he brings expertise in digital transformation, smart manufacturing, autonomous driving, and renewable energy to drive TDengine's solution strategy. Prior to joining TDengine, he worked as the Director of Product Marketing for PTC's IoT Division and Hexagon's Smart Manufacturing Division. He is currently based in California, USA.
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TDengine™ is a time-series database purpose-built for Industry 4.0 and Industrial IoT. It enables real-time ingestion, storage, analysis, and distribution of petabytes of data per day, generated by billions of sensors and data collectors. With TDengine making big data accessible, valuable, and affordable, digital transformation has never been easier.
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# TDengine 3.3.5.0 Release Notes
TDengine Team
January 8, 2025
## About TDengine
TDengine is a time-series database purpose-built for Industry 4.0 and Industrial IoT. It enables real-time ingestion, storage, analysis, and distribution of petabytes of data per day, generated by billions of sensors and data collectors. With TDengine making big data accessible, valuable, and affordable, digital transformation has never been easier.
## What’s New
* **Integration with Apache Superset:** You can now use data stored in TDengine with Apache Superset, a modern data exploration and visualization platform. For more information, see .
* **Embedded Grafana dashboards in taosExplorer:** You can configure one or more Grafana dashboards to display monitoring data for your TDengine cluster and view them within taosExplorer.
* **Updated compression settings:** The default settings for data compression have been updated based on extensive internal testing. The updated defaults reduce compressed data size in most scenarios. For more information, see .
* **(TDengine Enterprise only) Improved `COMPACT` experience:** The `COMPACT` command for database defragmentation can now be run automatically. You can also view the progress of a `COMPACT` operation and specify a desired concurrency.
**Note:** Password requirements for TDengine users have been made more strict in TDengine 3.3.5.0. See  for more information on the specific requirements.
## Compatibility
* You can deploy TDengine Enterprise 3.3.5.0 on mainstream Linux distributions and Windows.
* You can deploy TDengine OSS Server 3.3.5.0 on mainstream Linux distributions and macOS.
* You can deploy TDengine OSS Client 3.3.5.0 on mainstream Linux distributions, macOS, and Windows.
You can also run TDengine in Kubernetes or in Docker containers. See  for details about the compatibility of TDengine 3.3.5.0 with various architectures and operating systems.
**Note:** You must upgrade existing clients to TDengine 3.3.5.0 before connecting to a TDengine 3.3.5.0 server.
## Upgrading to TDengine 3.3.5.0
### Upgrading TDengine OSS
You can upgrade TDengine OSS to version 3.3.5.0 from version 3.0.1.5 or later.
To upgrade TDengine OSS, first back up your deployment by making a copy of the TDengine directory. After verifying that your deployment has been backed up, install TDengine 3.3.5.0 as described in the . It is not necessary to uninstall TDengine before upgrading.
**Note:** If you have deployed TDengine as a cluster, you must shut down and upgrade all nodes in the cluster to TDengine 3.3.5.0. Rolling upgrades are not supported in TDengine 3.3.5.0.
### Upgrading TDengine Enterprise and TDengine Cloud
Contact your account representative for assistance in upgrading TDengine Enterprise or TDengine Cloud.
You can check your current version of TDengine at any time by running the `SELECT SERVER_VERSION();` command.
## Resolved Issues
For a full list of issues resolved in this release, see .
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