TDengine

TDengine is built for industrial organizations that need to move beyond legacy historians. It combines a high-performance time-series database with an industrial data management layer, giving engineers a single platform to ingest, store, contextualize, and analyze large-scale operational data.

The open-source core (TDengine TSDB) handles the heavy lifting: a specialized storage engine tuned for time-series workloads that claims 10x the performance of general-purpose databases at a fraction of the storage cost. Automated tiered storage and S3 support keep the data footprint manageable as data volumes grow.

On top of the database sits the historian layer, which is where TDengine differentiates itself from tools like InfluxDB or GreptimeDB:

• Industrial connectivity via OPC, MQTT, and Kafka with built-in ETL for cleaning and transforming data at ingestion
• Asset contextualization through a tree hierarchy, reusable templates, and rich metadata, so raw sensor data becomes meaningful operational context
• Stream analytics that continuously monitor data to generate KPIs and trigger alerts without manual rule configuration
• Process analytics including batch comparison, trend analysis, and correlation tools for root cause investigation
• AI-driven anomaly detection and forecasting powered by TDgpt, running directly inside the database without external tooling