TDengine Blog

View the latest articles about time-series databases and industrial data processing

Why Industrial Data Must Be Open — Without Losing Context

If industrial data platforms are not open, every new AI capability requires custom integration, making it difficult to keep up with the pace of innovation.

Jeff Tao

April 8, 2026 | Data Historian, AI-Native Industrial Data Foundation

AI-Driven Operational Insights: Removing the Barrier Between Data and Understanding

AI-driven operational insights remove the barrier to understanding data by making it possible to generate insights without requiring deep expertise in analytics or domain modeling.

Jeff Tao

April 7, 2026 | Data Historian, AI-Native Industrial Data Foundation

TDengine Expands Middle East Presence with Arabian Digital Solutions Partnership

TDengine today announced a partnership with Arabian Digital Solutions (ADS), a Saudi Arabia-based industrial automation and engineering company specializing in smart manufacturing and digital transformation.

TDengine Team

April 7, 2026 | News

TDengine IDMP Now Supports Spanish and Korean

We’re excited to announce that TDengine IDMP now supports Spanish and Korean, available starting in version 1.0.15.2.

TDengine Team

April 2, 2026 | News

Asset-Centric and Event-Centric Visualization: From Dashboards to Operational Understanding

What industrial users need is a new kind of visualization—one that is asset-centric, event-aware, insight-driven, and tightly integrated with the data foundation.

Jeff Tao

April 2, 2026 | AI-Native Industrial Data Foundation, Data Historian

Advanced Analytics in Industrial Systems: Beyond the Historian

Organizations increasingly expect systems to generate insights—detect anomalies, predict future behavior, identify patterns, explain deviations and analyze the root cause.

Jeff Tao

April 2, 2026 | AI-Native Industrial Data Foundation, Data Historian

Event-Centric + Asset-Centric: The Missing Link in Industrial Data

Assets define what exists. Events define what happens. Only when both are modeled together can we truly understand industrial operations—and only then can AI become genuinely useful.

Jeff Tao

March 30, 2026 | AI-Native Industrial Data Foundation, Data Historian

How AI Helps Engineers Move from OEE Monitoring to Root-Cause Analysis

A low OEE number by itself is not very useful. What matters is whether the loss is coming from uptime, speed, or quality, and whether the team can isolate the cause quickly enough to act.

Jim Fan

March 29, 2026 | Data Historian, Industrial Data

Powering a Next-Generation Digital Redrying Facility with TDengine

By comprehensively addressing performance bottlenecks in data ingestion, storage, and computation for massive time-series workloads, TDengine has made the redrying process more digitalized, transparent, and intelligent.

TDengine Team

March 27, 2026 | Case Studies, Manufacturing

Building a Foundation for AI-Driven Manufacturing at Kunming Cigarette Factory

This project has validated TDengine’s suitability for handling massive time-series data in the tobacco industry, providing a reusable technical approach for digital transformation across the sector.

TDengine Team

March 27, 2026 | Case Studies, Manufacturing

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