Sensors on factory floors, wind turbines, and connected vehicles produce readings every second, and Apache IoTDB is the time-series database built to store those readings and answer questions over them. Devices write through client sessions that tolerate out-of-order, delayed, and multi-frequency arrivals, so a gateway that reconnects after an outage can backfill history without corrupting the timeline. Series live in a device hierarchy you can browse like a directory tree, or in tables queried with standard SQL, common table expressions, set operations, and more than one hundred built-in aggregation and time-series functions. The TsFile columnar format shares one time column across aligned series and applies encodings designed for sensor data, which keeps high-frequency archives compact while Spark and Hadoop jobs read the same files directly for larger analysis. Pipe synchronization streams records or transfers whole TsFiles between edge sites and central clusters with path and device filtering, so plants keep collecting locally while headquarters queries a continuous copy. AINode brings forecasting, anomaly detection, and missing-value imputation into the database itself: register a model with SQL, then ask for predictions in the same query language instead of shipping measurements to a separate machine learning service. A low-memory Edge edition runs collection on constrained gateways, and clusters scale by adding DataNodes under ConfigNode coordination with automatic load balancing. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.