Skip to content


Feature Views define features as a view on top of of your underlying data sources. Feature Views with Materialization enabled will precompute feature values in Tecton's online and offline stores to enable fast access to the feature values during training and inference.


When materialization is enabled in a Feature View, Tecton will orchestrate jobs that precompute the the results of queries defined by a Feature View and write the results to Tecton-managed stores: the Online and the Offline Feature Store:

  • Online Store: a low-latency key-value store containing the most recent version of feature data. This data is used to serve features to models for low-latency predictions.

  • Offline Store: a high volume, low cost store containing historical feature values. This data will is typically used for batch processes such as creating training data sets.

Types of Materialization

Tecton handles backfill and steady-state materialization for batch and stream features based on your Feature View configuration.

Steady-state Materialization

Steady-state Materialization refers to materialization being performed on new data arriving in real-time. Steady State Materialization continuously occurs on all FeatureViews where Materialization is enabled.

When a FeatureView has materialization enabled, Tecton will schedule steady-state materialization jobs on an ongoing basis in order to maintain fresh feature values. The frequency of steady-state materialization is controlled by the batch_schedule parameter.

Backfill Materialization

Backfill refers to any materialization operations performed on data in the past. There are two Backfill operations.

The initial materialization of a Feature View is referred to as a bootstrap backfill. During a bootstrap materialization, existing raw data is processed into feature values.

When materialization is initially enabled for a Feature View, Tecton performs a bootstrap materialization. The amount of data materialized during a bootstrap is controlled by the feature_start_time parameter.

Enabling Feature View Materialization

Every Batch and Stream Feature Views can enable materialization to the online and/or offline store by setting online=True and/or offline=True in the Feature View annotation parameters. These options are available for the following types of Feature Views:

On-Demand Feature Views cannot be materialized since they are calculated only at request-time.


Tecton provides tools to monitor and debug production Feature Views via the Web UI, SDK, and CLI. More information on monitoring is available in Monitoring Materialization.

Next: Learn about Workspaces →