ChronusQL language guide
Reason about streams in time.
A complete guide to the ChronusQL language, from a first projection to stateful windows, ordered event patterns, statistical enrichment, and online temporal models.
SELECT driver, AVG(speed) AS avg_speed
INTO output
FROM telemetry TIMESTAMP BY ts
GROUP BY driver, TumblingWindow(Duration(second, 10))Time aware SQL Language
ChronuSQL allows you to operate events over time.
This documentation gives you a brief introduction to ChronuSQL and its capabilities, including how records are addressed, how event time affects execution, how state is partitioned, when results are emitted, and which grammar forms are supported.
Documentation map
Build understanding in layers.
Start with the stream and event-time model, then move into stateful and predictive language only when the problem requires it.
Time windowed event analysis
Time as a first-class language.
TIMESTAMP BY, WINDOW BY, and windowing constructs make time a first-class concept in the language, allowing the system to timestamp, order, aggregate, and compute data according to temporal semantics. Together, they enable queries to move through time and compute information across different time slices using multiple windowing strategies.
Look into time windowsSELECT driver,
Window.EndTime AS session_end,
COUNT(*) AS event_count
INTO output
FROM laps TIMESTAMP BY ts
GROUP BY driver,
TumblingWindow(Duration(minute, 2))