dbt-materialize 1.3.1

The Materialize adapter plugin for dbt.

dbt-materialize

dbt adapter for Materialize.

For a complete step-by-step guide on how to use dbt and Materialize, check the documentation.

Installation

dbt-materialize is available on PyPI. To install the latest version via pip (optionally using a virtual environment), run:

python3 -m venv dbt-venv         # create the virtual environment
source dbt-venv/bin/activate     # activate the virtual environment
pip install dbt-materialize      # install the adapter

Requirements

dbt-materialize requires Materialize v0.28.0+.

Configuring your profile

To connect to a Materialize instance, use the reference profile configuration in your connection profile:

dbt-materialize:
  target: dev
  outputs:
    dev:
      type: materialize
      threads: 1
      host: [host]
      port: [port]
      user: [[e-mail]]
      pass: [password]
      dbname: [database]
      schema: [dbt schema]
      cluster: [cluster] # default 'default'
      sslmode: require
      keepalives_idle: 0 # default 0

Complete sample profiles can be found in sample_profiles.yml.

Supported Features

Materializations

Type	Supported?	Details
source	YES	Creates a source.
view	YES	Creates a view.
materializedview	YES	Creates a materialized view.
table	YES	Creates a materialized view. (Actual table support pending #5266.)
sink	YES	Creates a sink.
ephemeral	YES	Executes queries using CTEs.
incremental	NO	Use the materializedview materialization instead! dbt's incremental models are valuable because they only spend your time and money transforming your new data as it arrives. Luckily, this is exactly what Materialize's materialized views were built to do! Better yet, our materialized views will always return up-to-date results without manual or configured refreshes. For more information, check out our documentation.

Indexes

Use the indexes option to define a list of indexes on source, view, or materialized view materializations. Each Materialize index can have the following components:

Component	Value	Description
columns	list	One or more columns on which the index is defined. To create an index that uses all columns, use the default component instead.
name	string	The name for the index. If unspecified, Materialize will use the materialization name and column names provided.
cluster	string	The cluster to use to create the index. If unspecified, indexes will be created in the cluster used to create the materialization.
default	bool	Default: False. If set to True, creates a default index that uses all columns.

Additional macros

Macro	Purpose
mz_generate_name(identifier)	(Deprecated) Generates a fully-qualified name given an object name. Use the native Jinja function {{ this }} to reference relations instead.

We provide a materialize-dbt-utils package with Materialize-specific implementations of dispatched macros from dbt-utils. To use this package in your dbt project, check the latest installation instructions in dbt Hub.

Seeds

dbt seed will create a static materialized view from a CSV file. You will not be able to add to or update this view after it has been created.

Hooks

Not tested.

Custom Schemas

Not tested.

Sources

You can instruct dbt to create a dbt source in Materialize using the custom source materialization, which allows for injecting the complete source statement into your .sql file.

source freshness is not supported because using Materialize, your sources will always be fresh.

Documentation

dbt docs is supported.

Testing

dbt test is supported.

If you set the optional --store-failures flag or store-failures config, dbt will save the results of a test query to a materializedview. These will be created in a schema suffixed or named dbt_test__audit by default. Change this value by setting a schema config.

Snapshots

Not supported. Support is not planned for the near term.

Contributors

A huge thank you to Josh Wills, who created the original version of this adapter.