New Release: Approval flows for Kubernetes, Prisma support, and more!
Hey everyone!
We are excited to announce the release of Atlas v0.29, which continues our journey to make working with database easier, safer and more reliable. This release includes several significant updates that we are happy to share with you:
-
Approval flows for the Kubernetes Operator: Moving to a declarative way of managing database schemas has plenty of advantages, but many teams want to see and approve changes before they are applied. Doing this from the CLI is straightforward, but until recently it was not easy to provide this experience in Kubernetes-based workflows.
With the new approval flows, you can now review and approve schema migrations seamlessly, ensuring database changes are well-governed while maintaining deployment velocity.
-
Prisma support: Following our integrations with some of the most popular ORMs in our industry, we are happy to announce our official guide on using Atlas to manage database schemas for Prisma projects.
-
GitLab CI/CD Components: Integrating GitLab CI with Atlas just got much easier with the new GitLab CI/CD components.
-
IntelliJ Plugin: Our IntelliJ plugin has been upgraded with code folding, inline SQL syntax highlighting and suggestions, and syntax highlighting within heredoc clauses.
-
Timeseries Engine support for ClickHouse: ClickHouse users can now explore beta support for timeseries data in Atlas.
-
Constraint Triggers support for PostgreSQL: PostgreSQL users can now manage constraint triggers with Atlas.
Approval Flows for the Kubernetes Operator
Moving to a declarative way of managing database schemas has plenty of advantages, but many teams want to see and approve changes before they are applied.
Providing flows for keeping a human-in-the-loop from the CLI is straightforward, but until recently it was not easy to provide this experience in Kubernetes-based workflows.
Following our recent KubeCon session, the Atlas Operator now includes approval flows for declarative schema migrations, making database changes in Kubernetes safer:
- Pre-approvals - with pre-approvals, teams enhance their CI pipelines to detect schema changes and integrate their planning and approval in the code review process. The approved policies are then applied to the database by the operator.
- Ad-hoc Approvals - with ad-hoc approvals, the operator pauses the migration process and waits for human approval before applying the schema change. This is useful for schema changes that were not approved in advance or for projects that do not have a strict pre-approval policy.
Prisma Support
Following popular demand from the Atlas community, we are excited to announce our official guide on using Atlas to manage database schemas for Prisma projects.
Prisma already has an excellent migration tool called prisma migrate
, so why would you want to use Atlas with Prisma?
In many cases, Prisma's migrate
indeed checks all the boxes for managing your database schema. However, being tightly
coupled with the Prisma ORM, some use cases might require a dedicated schema management tool that can be used across
different ORMs and frameworks.
This guide shows how to load your existing prisma.schema
file into Atlas, manage your schema changes, and apply them to
your database using the Atlas CLI.
Interested in learning more? Read the guide!
Gitlab CI/CD Components
Integrating GitLab CI with Atlas just got much easier with our new GitLab CI/CD components.
GitLab CI/CD components are reusable YAML templates that you can use in your GitLab CI/CD pipelines to automate workflows within your GitLab project. Our newly published components are designed to simplify the process of integrating Atlas with GitLab CI/CD pipelines, enabling you to automate database schema management tasks with ease.
Want to learn more? Read the tutorial.
IntelliJ Plugin
Our IntelliJ plugin has been upgraded with code folding, inline SQL syntax highlighting and suggestions, and syntax highlighting within heredoc clauses. Our goal with these efforts is to make writing real world database applications with Atlas easier and more enjoyable.
If you use JetBrains editors, be sure to download the most recent version.
Timeseries Data Support for ClickHouse
ClickHouse recently added support for an experimental TimeSeries engine, which is designed to optimize storage and query performance for time-series data.
Atlas now supports this experimental feature, enabling ClickHouse users to manage schemas for their time-series data tables with ease:
You can simply define a TimeSeries
table in your Atlas schema.
table "example" {
schema = schema.public
engine = TimeSeries
}
PostgreSQL Constraint Triggers
The CONSTRAINT TRIGGER
is a PostgreSQL extension of the SQL standard, which works like a regular trigger but allows its execution time to be dynamically controlled using the SET CONSTRAINTS
command.
Starting with this version, users can define constraint triggers, and Atlas will manage their lifecycles. Their definitions are also supported in the Atlas HCL syntax:
trigger "users_insert" {
on = table.users
constraint = true
before {
insert = true
}
// ...
}
trigger "groups_insert" {
on = table.users
constraint = true
deferrable = INITIALLY_DEFERRED
before {
insert = true
}
// ...
}
Read more about the Storage Engine
Wrapping Up
We hope you enjoy the new features and improvements. As always, we would love to hear your feedback and suggestions on our Discord server.