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Announcing Atlas v0.3.2: multi-schema support

· 9 min read

Last week we released v0.3.2 of the Atlas CLI.

Atlas is an open source tool that helps developers manage their database schemas. Atlas plans database migrations for you based on your desired state. The two main commands are inspect and apply. The inspect command inspects your database and the apply command runs a migration by providing an HCL document with your desired state.

The most notable change in this version is the ability to interact with multiple schemas in both database inspection and migration (the apply command).

Some other interesting features include:

  • schema apply --dry-run - running schema apply in dry-run mode connects to the target database and prints the SQL migration to bring the target database to the desired state without prompting the user to approve it.
  • schema fmt - adds basic formatting capabilities to .hcl files.
  • schema diff - Connects to two given databases, inspects them, calculates the difference in their schemas, and prints a plan of SQL statements needed to migrate the "from" database to the state of the "to" database.

In this post we will explore the topic of multi-schema support. We will start our discussion with a brief explanation of database schemas, next we'll present the difference between how MySQL and PostgreSQL treat "schemas". We will then show how the existing schema inspect and schema apply commands work with multi-schema support, and wrap up with some plans for future releases.

What is a database schema?

Within the context of relational (SQL) databases, a database schema is a logical unit within a physical database instance (server/cluster) that forms a namespace of sorts. Inside each schema you can describe the structure of the tables, relations, indexes and other attributes that belong to it. In other words, the database schema is a "blueprint" of the data structure inside a logical container (Note: in Oracle databases a schema is linked to the user, so it carries a different meaning which is out of scope for this post). As you can guess from the title of this post, many popular relational databases allow users to host multiple (logical) schemas on the same (physical) database.

Where are database schemas used in practice?

Why is this level of logical division necessary? Isn't it enough to be able physically split data into different database instances? In my career, I've seen multiple scenarios in which organizations opt to split a database into multiple schemas.

First, grouping different parts of your application into logical units makes it simpler to reason about and govern. For instance, it is possible to create multiple user accounts in our database and give each of them permission to access a subset of the schemas in the database. This way, each user can only touch the parts of the database they need, preventing the practice of creating an almighty super-user account that has no permission boundary.

An additional pattern I've seen used, is in applications with a multi-tenant architecture where each tenant has its own schema with the same exact table structure (or some might have a different structure since they use different versions of the application). This pattern is used to create a stronger boundary between the different tenants (customers) preventing the scenario where one tenant accidentally has access to another's data that is incidentally hosted on the same machine.

Another useful feature of schemas is the ability to divide the same server into different environments for different development states. For example, you can have a "dev" and "staging" schema inside the same server.

What are the differences between schemas in MySQL and PostgreSQL?

A common source of confusion for developers (especially when switching teams or companies) is the difference between the meaning of schemas in MySQL and PostgreSQL. Both are currently supported by Atlas, and have some differences that should be clarified.

Looking at the MySQL glossary, it states:

"In MySQL, physically, a schema is synonymous with a database. You can substitute the keyword SCHEMA instead of DATABASE in MySQL SQL syntax, for example using CREATE SCHEMA instead of CREATE DATABASE"

As we can see, MySQL doesn't distinguish between schemas and databases in the terminology, but the underlying meaning is still the same - a logical boundary for resources and permissions.

To demonstrate this, open your favorite MySQL shell and run:

mysql> create schema atlas;
Query OK, 1 row affected (0.00 sec)

To create a table in our new schema, assuming we have the required permissions, we can switch to the context of the schema that we just created, and create a table:

USE atlas;
CREATE table some_name (
id int not null

Alternatively, we can prefix the schema, by running:

CREATE TABLE atlas.cli_versions
id bigint auto_increment primary key,
version varchar(255) not null

This prefix is important since, as we said, schemas are logical boundaries (unlike database servers). Therefore, we can create references between them using foreign keys from tables in SchemaA to SchemaB. Let's demonstrate this by creating another schema with a table and connect it to a table in the atlas schema:


CREATE TABLE atlantis.ui_versions
id bigint auto_increment
primary key,
version varchar(255) not null,
atlas_version_id bigint null,
constraint ui_versions_atlas_version_uindex
unique (atlas_version_id)

Now let's link atlantis to atlas:

alter table atlantis.ui_versions
add constraint ui_versions_cli_versions_id_fk
foreign key (atlas_version_id) references atlas.cli_versions (id)
on delete cascade;

That's it! We've created 2 tables in 2 different schemas with a reference between them.

How does PostgreSQL treat schemas?

When booting a fresh PostgreSQL server, we get a default logical schema called "public". If you wish to split your database into logical units as we've shown with MySQL, you can create a new schema:


Contrary to MySQL, Postgres provides an additional level of abstraction: databases. In Postgres, a single physical server can host multiple databases. Unlike schemas (which are basically the same as in MySQL) - you can't reference a table from one PostgreSQL database to another.

In Postgres, the following statement will create an entirely new database, where we can place different schemas and tables with that may contain references between them:

create database releases;

When we run this statement, the database will be created with the default Postgres metadata tables and the default public schema.

In Postgres, you can give permissions to an entire database(s), schema(s), and/or table(s), and of course other objects in the Postgres schema.

Another distinction from MySQL is that in addition to sufficient permissions, a user must have the schema name inside their search_path in order to use it without a prefix.

To sum up, both MySQL and Postgres allow the creation of separate logical schemas within a physical database server, schemas can refer to one another via foreign-keys. PostgreSQL supports an additional level of separation by allowing users to create completely different databases on the server.

Atlas multi-schema support

As we have shown, having multiple schemas in the same database is a common scenario with popular relational databases. Previously, the Atlas CLI only supported inspecting or applying changes to a single schema (even though this has been long supported in the Go API). With this release, we have added support for inspecting and applying multiple schemas with a single .hcl file.

Next, let's demonstrate how we can use the Atlas CLI to inspect and manage a database with multiple schemas.

Start by downloading and installing the latest version of the CLI. For the purpose of this demo, we will start with a fresh database of MySQL running in a local docker container:

docker run --name atlas-db  -p 3306:3306 -e MYSQL_ROOT_PASSWORD=pass -e MYSQL_DATABASE=example mysql:8

By passing example in the MYSQL_DATABASE environment variable a new schema named "example" is created. Let's verify this by using the atlas schema inspect command. In previous versions of Atlas, users had to specify the schema name as part of the DSN for connecting to the database, for example:

atlas schema inspect -u "mysql://root:pass@localhost:3306/example"

Starting with v0.3.2, users can omit the schema name from the DSN to instruct Atlas to inspect the entire database. Let's try this:

$ atlas schema inspect -u "mysql://root:pass@localhost:3306/" > atlas.hcl
cat atlas.hcl
schema "example" {
charset = "utf8mb4"
collation = "utf8mb4_0900_ai_ci"

Let's verify that this works correctly by editing the atlas.hcl that we have created above and adding a new schema:

schema "example" {
charset = "utf8mb4"
collation = "utf8mb4_0900_ai_ci"
schema "example_2" {
charset = "utf8mb4"
collation = "utf8mb4_0900_ai_ci"

Next, we will use the schema apply command to apply our changes to the database:

atlas schema apply -u "mysql://root:pass@localhost:3306/" -f atlas.hcl

Atlas plans a migration to add the new DATABASE (recall that in MySQL DATABASE and SCHEMA are synonymous) to the server, when prompted to approve the migration we choose "Apply":

-- Planned Changes:
-- Add new schema named "example_2"
✔ Apply

To verify that schema inspect works properly with multiple schemas, lets re-run:

atlas schema inspect -u "mysql://root:pass@localhost:3306/"

Observe that both schemas are inspected:

schema "example" {
charset = "utf8mb4"
collation = "utf8mb4_0900_ai_ci"
schema "example_2" {
charset = "utf8mb4"
collation = "utf8mb4_0900_ai_ci"

To learn more about the different options for working with multiple schemas in inspect and apply commands, consult the CLI Reference Docs.

What's next for multi-schema support?

I hope you agree that multi-schema support is a great improvement to the Atlas CLI, but there is more to come in this area. In our previous blogpost we have shared that Atlas also has a Management UI (-w option in the CLI) and multi-schema support is not present there yet - stay tuned for updates on multi-schema support for the UI in an upcoming release!

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