Thyme
Concepts

Concepts Overview

The four primitives that make up a Thyme feature pipeline.

Thyme is built around four primitives. You use all four when defining a feature pipeline.

PrimitiveWhat it isDefined with
DatasetA named, schema'd stream of events@dataset
PipelineA windowed aggregation over a dataset@pipeline + @inputs
FeaturesetA collection of model-ready features@featureset + @extractor
SourceA connector that feeds raw events into a dataset@source

How they connect

Source → Dataset (raw events)
           ↓  @pipeline
         Dataset (aggregated stats)
           ↓  @extractor
         Featureset (model features)
           ↓
         Query Server → model

A source ingests raw events into a dataset. A pipeline aggregates that dataset into another dataset. An extractor reads the aggregated dataset and composes the final features that your model queries.

Learn more

Your First Feature

A detailed walkthrough building your first feature end-to-end.

Datasets

Schema, keys, timestamps, and indexing for Thyme datasets.

On this page

How they connectLearn more