Developer guide

This guide details what you'll need to contribute to Materialize.

Materialize consists of several services written in Rust that are orchestrated by Kubernetes. Supporting build and test tools are written in a combination of Rust, Python, and Bash. Tests often use Docker Compose rather than Kubernetes to orchestrate interactions with other systems, like Apache Kafka.

Install build and test dependencies

C components

Materialize depends on several components that are written in C and C++, so you'll need a working C and C++ toolchain. You'll also need to install:

The CMake build system
libclang
PostgreSQL
lld (on Linux, or set a custom RUSTFLAGS)

On macOS, if you install Homebrew, you'll be guided through the process of installing Apple's developer tools, which includes a C compiler and libclang. Then it's a cinch to install CMake and PostgreSQL.

brew install cmake postgresql

On Debian-based Linux variants, it's even easier:

sudo apt update
sudo apt install build-essential cmake postgresql-client libclang-dev lld

On other platforms, you'll have to figure out how to get these tools yourself.

Rust

Install Rust via rustup:

curl https://sh.rustup.rs -sSf | sh

We recommend that you do not install Rust via your system's package manager. We closely track the most recent version of Rust. The version of Rust in your package manager is likely too old to build Materialize.

For details on how we upgrade Rust see here.

Docker

Materialize's tests mostly require Docker and Docker Compose to be installed. On macOS it is part of Docker Desktop or Orbstack:

brew install --cask orbstack

On Debian-based Linux both Docker and the Docker Compose plugin have to be installed:

sudo apt update
sudo apt install docker docker-compose-plugin

Metadata store

Running Materialize locally requires a running Postgres / CockroachDB server.

On macOS, when using Homebrew, CockroachDB can be installed and started via:

brew install materializeinc/cockroach/cockroach
brew services start cockroach

(We recommend use of our forked Homebrew tap because it runs CockroachDB using an in-memory store, which avoids slow filesystem operations on macOS.)

On Linux, we recommend using Docker:

docker run --name=cockroach -d -p 127.0.0.1:26257:26257 -p 127.0.0.1:26258:8080 cockroachdb/cockroach:v23.1.11 start-single-node --insecure

If you can successfully connect to CockroachDB with either psql postgres://root@localhost:26257 or cockroach sql --insecure, you're all set.

Eatmydata

If you are just testing Materialize locally and don't care about data loss you can run environmentd with eatmydata environmentd, which will disable fsync calls.

Similarly postgres as the metadata store can be instructed to eat your data using echo LD_PRELOAD=libeatmydata.so > /etc/postgresql/18/main/environment, and then restarting it.

On my Linux system without eatmydata for both Materialize and Postgres, running with bin/environmentd --reset --optimized --no-default-features --postgres=postgres://deen@%2Fvar%2Frun%2Fpostgresql:

DROP TABLE
Time: 105.810 ms
CREATE TABLE
Time: 163.484 ms

After enabling eatmydata in Materialize and Postgres:

DROP TABLE
Time: 7.951 ms
CREATE TABLE
Time: 10.459 ms

Or in mzcompose:

docker pull --no-cache materialize/materialized:latest
docker run -it --env MZ_EAT_MY_DATA=1 -p 127.0.0.1:6875:6875 materialize/materialized:latest

Before:

DROP TABLE
Time: 133.021 ms
CREATE TABLE
Time: 111.492 ms

After:

DROP TABLE
Time: 6.504 ms
CREATE TABLE
Time: 8.773 ms

Python

Materialize's build and test infrastructure is largely written in Python; running our integration tests, in particular, requires a local Python environment. Most of this should be taken care of by the bin/pyactivate script, which constructs a local virtual environment and keeps necessary dependencies up to date.

We support, as a minimum version, the default Python provided in the most recent Ubuntu LTS release. As of January 2026 this is Python 3.12, provided in Ubuntu 24.04 "Noble Numbat". Earlier versions may work but are not supported. Our recommended installation methods are:

macOS: Homebrew + uv
1. brew install uv
2. uv python install 3.13
Linux: System package manager if possible, or community package repositories if necessary
Windows: Microsoft App Store

If none of the above work well for you, these are a few other methods that have worked for us in the past, but are not formally supported:

Confluent Platform

The Confluent Platform bundles Apache ZooKeeper and Apache Kafka with several non-free Confluent tools, like the Confluent Schema Registry and Control Center. For local development, the Confluent CLI allows easy management of these services.

Confluent Platform is not required for changes that don't need Kafka integration. If your changes don't affect integration with external systems and can be fully exercised by SQL logic tests, we recommend not installing the Confluent Platform, as it is a rather heavy dependency. Most Materialize employees, or other major contributors, will probably need to run the full test suite and should therefore install the Confluent Platform.

All platforms

First, install the CLI. As of early July 2022 you can run this command on macOS and Linux:

curl -sL --http1.1 https://cnfl.io/cli | sudo sh -s -- -b /usr/local/bin latest

If this no longer works, follow the instructions in the Confluent CLI documentation. Then please update this guide with the new instructions!

macOS

The easiest way to install this is via Homebrew:

brew install confluentinc/tap/cli

Linux

On Debian-based Linux variants, you can use APT to install Java and the Confluent Platform:

curl http://packages.confluent.io/deb/8.2/archive.key | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://packages.confluent.io/deb/8.2 stable main"
sudo apt update
sudo apt install openjdk-21-jre-headless confluent-community-2.13
echo export CONFLUENT_HOME=/ >> ~/.bashrc
source ~/.bashrc
confluent local services start

On other Linux variants, you'll need to make your own way through Confluent's installation instructions. Note that, at the time of writing (last update March 2026), Java LTS 11, 17, and 21 are supported.

Alternatively, it is possible to get an all-in-one tarball from here. Then untar this to a location, set $CONFLUENT_HOME to this location and add $CONFLUENT_HOME/bin to your $PATH. I found this to be the most convenient way to get confluent and it also works in a distro neutral way (if you are using, Arch Linux for example).

Nix

Optionally, you can use nix to install all required dependencies on both Linux and macOS, using the provided shell.nix. Install nix and use nix-shell to enter an environment that is isolated from the main OS.

nix-shell misc/nix/shell.nix
[nix-shell]$ rustup install stable # If not installed already

Materialize can then be built inside this shell. Note that CockroachDB is not included in the above configuration and needs to be installed separately, as described above. Also, IDEs will not be able to access the installed dependencies unless they are started from within the nix-shell environment:

# Linux
[nix-shell]$ code .
# macOS
[nix-shell]$ open -na "RustRover"
[nix-shell]$ open -na "Visual Studio Code"

Note that on macOS, the mzcompose tests fail to run from within nix-shell, as our config does not yet set up cross-compilation support for x86-64 needed to run mzcompose.

Building Materialize

First, clone this repository:

git clone git@github.com:MaterializeInc/materialize.git

Because the MaterializeInc organization requires two-factor authentication (2FA), you'll need to clone via SSH as indicated above, or configure a personal access token for use with HTTPS.

Then you can build Materialize. Because Materialize is a collection of several Rust services that need to be built together, each service can be built individually via Cargo, but we recommend using the bin/environmentd script to drive the process:

cd materialize
bin/environmentd [--release] [--optimized] [<environmentd arg>...]

WebAssembly / WASM

Some crates are compiled to WebAssembly and published to npm. This is accomplished through wasm-pack. Install it by running:

cargo install wasm-pack

WASM builds can then be initiated through

./bin/wasm-build <path/to/crate>

WASM crates reside in misc/wasm/ Cargo workspace, and should be kept out of the main Cargo workspace to avoid cache invalidation issues.

Running Confluent Platform

As mentioned above, Confluent Platform is only required need to test Kafka sources and sinks against a local Kafka installation. If possible, we recommend that you don't run the Confluent Platform if you don't need it, as it is very memory hungry.

If you do need the Confluent Platform running locally, execute the following commands:

confluent local services schema-registry start  # Also starts ZooKeeper and Kafka.

You can also use the included confluent CLI command to start and stop individual services. For example:

confluent local services status        # View what services are currently running.
confluent local services kafka start   # Start Kafka and any services it depends upon.
confluent local services kafka log     # View Kafka log file.

Beware that the CLI is fairly buggy, especially around service management. Putting your computer to sleep often causes the service status to get out of sync. In other words, trust the output of confluent local services <service> log and ps ... | grep over the output of confluent local services status. Still, it's reliable enough to be more convenient than managing each service manually.

When the confluent local services are running, they can be examined via a web UI which defaults to http://localhost:9021.

It might happen that the start script says that it failed to start zookeeper/kafka/schema-registry, but it actually starts them successfully, it just can't detect them for some reason. In this case, you can just run confluent local services schema-registry start 3 times, and then everything is up.

Running and connecting to local Materialize

Once things are built and CockroachDB is running, you can start Materialize:

bin/environmentd --reset -- --all-features --unsafe-mode

This should bootstrap a fresh Materialize instance. Once you see the logline "environmentd v listening...", you can connect to the database via:

psql -U materialize -h localhost -p 6875 materialize

This uses the external SQL port. If you wish to connect using a system account, you can use the internal port with the mz_system user:

psql -U mz_system -h localhost -p 6877 materialize

In order to run Materialize with large clusters and more memory available, you have to set a license key. Set export MZ_LICENSE_KEY=$HOME/license-key and write the materialize dev license key from 1Password into that file. In order to have mzcompose based tests pick up the license key, set export MZ_CI_LICENSE_KEY=$(cat $MZ_LICENSE_KEY).

Console UI

Console can point at your local environmentd. To use this feature, pass the internal console flag:

bin/environmentd -- --internal-console-redirect-url="https://local.console.materialize.com"

Then visit http://localhost:6878/internal-console/. This is a great way to dogfood the console, feedback is valuable.

Note there is no frontegg login in this mode, so all frontegg features are disabled.

Web UI

Materialize embeds a web UI, which it serves from port 6876. If you're running Materialize locally, you can view the web UI at http://localhost:6876.

Developing the web UI can be painful, as by default the HTML, CSS, and JS source code for the UI gets baked into the binary, and so making a change requires a full rebuild of the binary.

To speed up the development cycle, you can enable the dev-web feature like so:

cd src/environmentd
bin/environmentd --features=dev-web

In this mode, every request for a static file will reload the file from disk. Changes to standalone CSS and JS files will be reflected immediately upon reload, without requiring a recompile!

Note that dev-web can only hot-reload the files in src/environmentd/src/static. The HTML templates in src/environmentd/src/templates use a compile-time templating library called askama, and so changes to those templates necessarily require a recompile.

For details about adding a new JavaScript/CSS dependency, see the comment in src/environmentd/build/npm.rs.

Testing

Materialize's testing philosophy is sufficiently complex that it warrants its own document. See Developer guide: testing.

Style

We use the following tools to perform automatic code style checks:

Tool	Use	Run locally with
Clippy	Rust semantic nits	`cargo clippy`
rustfmt	Rust code formatter	`cargo fmt`
Linter	General formatting nits	`bin/lint`
cargo-udeps	Check for unused Rust dependencies	`bin/unused-deps`

See the style guide for additional recommendations on code style.

Required Tools

Linting requires the following tools and Cargo packages to be installed:

buf (installation guide)
shellcheck (installation guide)
npx (brew install node)
helm-docs (brew install norwoodj/tap/helm-docs)
trufflehog (brew install trufflehog)
cargo-about (cargo install cargo-about)
cargo-deplint (cargo install cargo-deplint)
cargo-deny (cargo install cargo-deny)

Submitting and reviewing changes

See Developer guide: submitting and reviewing changes.

Code organization

Repository structure

This repository has the following basic structure:

bin contains scripts for contributor use.
ci contains configuration and scripts for CI.
doc/developer contains documentation for Materialize contributors, including this document.
doc/user contains the user-facing documentation, which is published to https://materialize.com/docs.
misc contains a variety of supporting tools and projects. Some highlights:
- misc/dbt-materialize contains the Materialize dbt adapter.
- misc/python contains Python developer tools, like mzbuild.
- misc/nix contains an experimental Nix configuration for developing Materialize.
- misc/wasm contains the Rust crates that are published to NPM as WebAssembly.
- misc/www contains the source code for https://dev.materialize.com.
src contains the primary Rust crates that comprise Materialize.
test contains test suites, which are described in Developer guide: testing.

Rust crate structure

We break our Rust code into crates primarily to promote organization of code by team, thereby introducing ownership and autonomy. As such, many crates are owned by a specific team (which does not preclude the existence of shared, cross-team crates).

Although the primary unit of code organization at the inter-team level is the crate, modules within a crate are also useful for code organization, especially because they are the level at which pub visibility operates.

We make a best-effort attempt to document the ownership of the Rust code in this repository using GitHub's CODEOWNERS file.

You can create and view a relationship diagram of our crates by running the following command (this will require graphviz):

bin/crate-diagram

It is possible to view transitive dependencies of a select subset of roots by specifying the --roots flag with a comma separated list of crates:

bin/crate-diagram --roots mz-sql,mz-dataflow

Other repositories

Where possible, we prefer to keep things in the main repository (a "monorepo" approach). There are a few exceptions:

demos, which showcases several use cases for Materialize
rust-dec, libdecnumber bindings for Rust
materialize-dbt-utils, data build tool (dbt) utilities for Materialize
Several custom Pulumi providers

Don't add to this list without good reason! Separate repositories are acceptable for:

Rapid iteration on new Materialize plugins or integrations, where the CI time or code quality requirements in the main repository would be burdensome. When the code is more stable, the repository should be integrated into the main Materialize repository.
External requirements that require a separate repository. For example, Pulumi providers are conventionally developed each in their own repository. Similarly, materialize-dbt-utils can only appear on dbt hub if it is developed in a standalone repository.
Stable foundational components where community contribution is desirable. For example, rust-dec is a very small package, and asking contributors to clone the entire Materialize repository would be a large barrier to entry. Changes to Materialize very rarely require changes in rust-dec, so maintaining the two separately does not introduce much overhead.

Developer tools

Editors and IDEs

In principle, any text editor can be used to edit Rust code.

Visual Studio Code

By default, we recommend that developers without a strong preference of an editor use Visual Studio Code with the rust-analyzer plugin. This is the most mainstream setup for developing Materialize, and the one for which you are the most likely to be able to get help if something goes wrong.

Visual Studio Code also works well for editing Python; to work on the Python code in the Materialize repository, install the official Python extension from Microsoft and add the following to your settings.json.

{
  "python.linting.mypyEnabled": true,
  "python.analysis.extraPaths": [
      "misc/python"
  ],
  "python.defaultInterpreterPath": "misc/python/venv/bin/python"
}

If you prefer to use another editor, such as Vim or Emacs, we recommend that you install an LSP plugin with Rust-Analyzer. How to do so is beyond the scope of this document; if you have any issues, ask in one of the engineering channels on Slack.

If you are using Rust-Analyzer, you should configure it to conform to our style guide by setting the following options:

imports.granularity.group = module
imports.prefix = crate

RustRover

RustRover is another option for an IDE with good code navigation features. This is a good choice for developers who prefer the JetBrains ecosystem. This folder provides some example run configurations to help get started with running and debugging Materialize in RustRover.

If you are a Materialize employee, ask in the #jetbrains channel on Slack for access to a corporate JetBrains license. If you're not yet sure you want to use RustRover, you can use the 30-day free trial.

Editor add-ons

A few editor-specific add-ons and configurations have been authored to improve the editing of Materialize-specific code. Check misc/editor for add-ons that may be relevant for your editor of choice.

Debugging

The standard debuggers for Rust code are rust-lldb on macOS, and rust-gdb on GNU/Linux. (It is also possible to run rust-lldb on GNU/Linux if necessary for whatever reason). These are wrappers around lldb and gdb, respectively, that endow them with slightly improved capabilities for pretty-printing Rust data structures. Visual Studio Code users may want to try the CodeLLDB plugin.

Unfortunately, you will soon find that these programs work less well than the equivalent tools for some other mainstream programming languages. In particular, inspecting complex data structures is often tedious and difficult. For this reason, most developers routinely use println! statements for debugging, in addition to (or instead of) these standard debuggers.

Automatic style checks

To ensure each code change passes all style nits before pushing to GitHub, symlink pre-push into your local git hooks:

ln -s ../../misc/githooks/pre-push .git/hooks/pre-push

Shell completion

Some Materialize scripts have shell completion, and the latest versions of the completions files are checked in to misc/completions. The contents of this directory can be sourced into your shell, and will stay updated as any changes are made.

To add the completions to bash, add the following to your ~/.bashrc:

source /path/to/materialize/misc/completions/bash/*

For zsh, add the following to your ~/.zshrc before compinit:

fpath=(/path/to/materialize/misc/completions/zsh $fpath)

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Install build and test dependencies

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Developer guide

Install build and test dependencies

C components

Rust

Docker

Metadata store

Eatmydata

Python

Confluent Platform

All platforms

macOS

Linux

Nix

Building Materialize

WebAssembly / WASM

Running Confluent Platform

Running and connecting to local Materialize

Console UI

Web UI

Testing

Style

Required Tools

Submitting and reviewing changes

Code organization

Repository structure

Rust crate structure

Other repositories

Developer tools

Editors and IDEs

Visual Studio Code

RustRover

Editor add-ons

Debugging

Automatic style checks

Shell completion