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title: "Announcing v0.23: Redshift Support, CircleCI and More" | ||
authors: rotemtam | ||
tags: [release, redshift, circleci, gorm, sqlalchemy, erd] | ||
--- | ||
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import InstallationInstructions from '../../md/components/_installation_instructions.mdx' | ||
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Hi everyone, | ||
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It's been a few weeks since the release of [v0.22](https://github.com/ariga/atlas/releases/tag/v0.22.0), and we're | ||
excited to be back with the next version of Atlas, packed with some long awaited features and improvements. | ||
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* [Redshift](#redshift-support) Support - [Amazon Redshift](https://aws.amazon.com/redshift/), a fully managed, petabyte-scale data | ||
warehouse service in the cloud. Starting today, you can use Atlas to manage your Redshift Schema-as-Code. | ||
* [CircleCI Integration](#circleci-integration) - Following some recent requests from our Enterprise customers, we have | ||
added a CircleCI orb to make it easier to integrate Atlas into your CircleCI pipelines. | ||
* [Kubernetes Operator Down Migrations](#kubernetes-operator-down-migrations) - The Kubernetes Operator now detects when | ||
you are moving to a previous version and will attempt to apply a down migration if configured to do so. | ||
* [GORM View Support](#gorm-view-support) - We have added support for defining SQL Views in your GORM models. | ||
* [SQLAlchemy Provider Improvements](#sqlalchemy-provider-improvements) - We have added support for defining models using | ||
SQLAlchemy Core Tables in the SQLAlchemy provider. | ||
* [ERD v2](#erd-v2) - We have added a new navigation sidebar to the ERD to make it easier to navigate within large schemas. | ||
* [PostgreSQL Improvements](#other-improvements) - We have added support for PostgreSQL Event Triggers, Aggregate Functions, | ||
and Function Security. | ||
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Let's dive in! | ||
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### Redshift Beta Support | ||
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Atlas's "Database Schema-as-Code" is useful even for managing small schemas with a few tables, but it really shines when | ||
you have a large schema with many tables, views, and other objects. This is the common case instead of the exception | ||
when you are dealing with Data Warehouses like Redshift that aggregate data from multiple sources. | ||
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Data warehouses typically store complex and diverse datasets consisting of hundreds of tables with thousands of columns | ||
and relationships. Managing these schemas manually can be a nightmare, and that's where Atlas comes in. | ||
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Today we are happy to announce the beta support for Amazon Redshift in Atlas. You can now use Atlas to manage your | ||
Redshift schema, generate ERDs, plan and apply changes, and more. | ||
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To get started, first install the latest version of the Atlas CLI: | ||
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<InstallationInstructions/> | ||
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Next, login to your Atlas account to activate the Redshift beta feature: | ||
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```bash | ||
atlas login | ||
``` | ||
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To verify Atlas is able to connect to your Redshift database, run the following command: | ||
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```bash | ||
atlas schema inspect --url "redshift://<username>:<password>@<host>:<port>/<database>?search_path=<schema>" | ||
``` | ||
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If everything is working correctly, you should see the [Atlas DDL](/atlas-schema/hcl) representation of your Redshift schema. | ||
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To learn more about the Redshift support in Atlas, check out the [documentation](/guides/redshift). | ||
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### CircleCI Integration | ||
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CircleCI is a popular CI/CD platform that allows you to automate your software development process. With this version | ||
we have added a [CircleCI orb](https://circleci.com/developer/orbs/orb/ariga/atlas-orb) to make it easier to integrate | ||
Atlas into your CircleCI pipeline. [CircleCI orbs](https://circleci.com/orbs/) are reusable packages of | ||
YAML configuration that condense repeated pieces of config into a single line of code. | ||
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As an example, suppose you wanted to create a CircleCI pipeline that pushes your migration directory to your Atlas Cloud | ||
Schema Registry. You can use the `atlas-orb` to simplify the configuration: | ||
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```yaml | ||
version: '2.1' | ||
orbs: | ||
atlas-orb: ariga/[email protected] | ||
workflows: | ||
postgres-example: | ||
jobs: | ||
- push-dir: | ||
context: the-context-has-ATLAS_TOKEN | ||
docker: | ||
- image: cimg/base:current | ||
- environment: | ||
POSTGRES_DB: postgres | ||
POSTGRES_PASSWORD: pass | ||
POSTGRES_USER: postgres | ||
image: cimg/postgres:16.2 | ||
steps: | ||
- checkout | ||
- atlas-orb/setup: | ||
cloud_token_env: ATLAS_TOKEN | ||
version: latest | ||
- atlas-orb/migrate_push: | ||
dev_url: >- | ||
postgres://postgres:pass@localhost:5432/postgres?sslmode=disable | ||
dir_name: my-cool-project | ||
``` | ||
Let's break down the configuration: | ||
* The `push-dir` job uses the `cimg/postgres:16.2` Docker image to run a PostgreSQL database. | ||
This database will be used as the [Dev Database](/concepts/dev-database) for different operations | ||
performed by Atlas. | ||
* The `atlas-orb/setup` step initializes the Atlas CLI with the provided `ATLAS_TOKEN` environment variable. | ||
* The `atlas-orb/migrate_push` step pushes the migration directory `my-cool-project` to the Atlas Cloud Schema Registry. | ||
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To learn more about the CircleCI integration, check out the [documentation](https://circleci.com/developer/orbs/orb/ariga/atlas-orb). | ||
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### Kubernetes Operator Down Migrations | ||
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The [Atlas Operator](/integrations/kubernetes/operator) is a Kubernetes operator that enables you to manage your database | ||
schemas using Kubernetes Custom Resources. In one of our [recent releases](/blog/2024/04/01/migrate-down), we added | ||
support for the `migrate down` command to the CLI. Using this command, you can roll back applied migrations | ||
in a safe and controlled way, without using pre-planned down migration scripts or manual intervention. | ||
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Starting with [v0.5.0](https://github.com/ariga/atlas-operator/releases/tag/v0.5.0), the Atlas Operator supports | ||
down migrations as well. When you change the desired version of your database for a given `AtlasMigration` resource, the operator | ||
will detect whether you are moving to a previous version and will attempt to apply a down migration if you configured it | ||
to do so. | ||
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Down migrations are controlled via the new `protectedFlows` field in the `AtlasMigration` resource. This field allows you | ||
to specify the policy for down migrations. The following policy, for example, allows down migrations and auto-approves them: | ||
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```yaml | ||
apiVersion: db.atlasgo.io/v1alpha1 | ||
kind: AtlasMigration | ||
metadata: | ||
name: atlasmig-mysql | ||
spec: | ||
protectedFlows: | ||
migrateDown: | ||
allow: true | ||
autoApprove: true | ||
# ... redacted for brevity | ||
``` | ||
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Alternatively, Atlas Cloud users may set the `autoApprove` field to `false` to require manual approval for down migrations. | ||
In this case, the operator will pause the migration and wait for the user to approve the down migration before proceeding: | ||
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![](https://atlasgo.io/uploads/versioned/require-approval.png) | ||
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### ERD v2 | ||
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When you push your migration directory to the Atlas Cloud Schema Registry, Atlas generates an ERD for your schema. | ||
The ERD is a visual representation of your schema that shows the different database objects in your schema and the | ||
relationships between them. | ||
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To make it easier to navigate within large schemas we have recently added a fresh new navigation sidebar to the ERD: | ||
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![](https://atlasgo.io/uploads/blog/v0.23/erd-sidebar.png) | ||
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### GORM View Support | ||
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GORM is a popular ORM library for Go that provides a simple way to interact with databases. | ||
The [Atlas GORM provider](/guides/orms/gorm) provides a seamless integration between Atlas and GORM, allowing you to | ||
generate migrations from your GORM models and apply them to your database. | ||
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SQL Views are a powerful feature in relational databases that allow you to create virtual tables based on the result of | ||
a query. Managing views with GORM (and ORMs in general) is a notoriously clunky process, as they are normally not first-class | ||
citizens in the ORM world. | ||
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With [v0.4.0](https://github.com/ariga/atlas-provider-gorm/releases/tag/v0.4.0), we have added a new API to the GORM | ||
provider that allows you to define views in your GORM models. | ||
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Here's a glimpse of how you can define a view in GORM: | ||
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```go | ||
// User is a regular gorm.Model stored in the "users" table. | ||
type User struct { | ||
gorm.Model | ||
Name string | ||
Age int | ||
} | ||
// WorkingAgedUsers is mapped to the VIEW definition below. | ||
type WorkingAgedUsers struct { | ||
Name string | ||
Age int | ||
} | ||
func (WorkingAgedUsers) ViewDef(dialect string) []gormschema.ViewOption { | ||
return []gormschema.ViewOption{ | ||
gormschema.BuildStmt(func(db *gorm.DB) *gorm.DB { | ||
return db.Model(&User{}).Where("age BETWEEN 18 AND 65").Select("name, age") | ||
}), | ||
} | ||
} | ||
``` | ||
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By implementing the `ViewDefiner` interface, GORM users can now include views in their GORM models and have Atlas | ||
automatically generate the necessary SQL to create the view in the database. | ||
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To learn more about the GORM view support, check out the [documentation](https://github.com/ariga/atlas-provider-gorm?tab=readme-ov-file#views). | ||
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Thanks to [luantranminh](https://github.com/luantranminh) for contributing this feature! | ||
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### SQLAlchemy Provider Improvements | ||
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The [Atlas SQLAlchemy provider](/guides/orms/sqlalchemy) allows you to generate migrations from your SQLAlchemy models | ||
and apply them to your database. | ||
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With [v0.2.1](https://github.com/ariga/atlas-provider-sqlalchemy/releases/tag/v0.2.1), we have added support for defining | ||
models using [SQLAlchemy Core Tables](https://docs.sqlalchemy.org/en/20/core/metadata.html#module-sqlalchemy.schema) in | ||
addition to the existing support for ORM Models. | ||
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In addition, we have decoupled the provider from using a specific SQLAlchemy release, allowing users to use any version | ||
of SQLAlchemy they prefer. This should provide more flexibility and make it easier to integrate the provider into your | ||
existing projects. | ||
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Huge thanks to [vshender](https://github.com/vshender) for contributing these improvements! | ||
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### Other Improvements | ||
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On our quest to support the long tail of lesser known database features we have recently added support for the following: | ||
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#### PostgreSQL Event Triggers | ||
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PostgreSQL [Event Triggers](https://www.postgresql.org/docs/current/event-triggers.html) are a special kind of | ||
trigger. Unlike regular triggers, which are attached to a single table and capture only DML events, event | ||
triggers are global to a particular database and are capable of capturing DDL events. | ||
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Here are some examples of how you can use event triggers in Atlas: | ||
```hcl | ||
# Block table rewrites. | ||
event_trigger "block_table_rewrite" { | ||
on = table_rewrite | ||
execute = function.no_rewrite_allowed | ||
} | ||
# Filter specific events. | ||
event_trigger "record_table_creation" { | ||
on = ddl_command_start | ||
tags = ["CREATE TABLE"] | ||
execute = function.record_table_creation | ||
} | ||
``` | ||
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#### Aggregate Functions | ||
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Aggregate functions are functions that operate on a set of values and return a single value. They are commonly used | ||
in SQL queries to perform calculations on groups of rows. PostgreSQL allows users to define custom aggregate functions | ||
using the `CREATE AGGREGATE` statement. | ||
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Atlas now supports defining custom aggregate functions in your schema. Here's an example of how you can define an | ||
aggregate function in Atlas: | ||
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```hcl {1-8} | ||
aggregate "sum_of_squares" { | ||
schema = schema.public | ||
arg { | ||
type = double_precision | ||
} | ||
state_type = double_precision | ||
state_func = function.sum_squares_sfunc | ||
} | ||
function "sum_squares_sfunc" { | ||
schema = schema.public | ||
lang = PLpgSQL | ||
arg "state" { | ||
type = double_precision | ||
} | ||
arg "value" { | ||
type = double_precision | ||
} | ||
return = double_precision | ||
as = <<-SQL | ||
BEGIN | ||
RETURN state + value * value; | ||
END; | ||
SQL | ||
} | ||
``` | ||
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#### Function Security | ||
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PostgreSQL allows you to define the security level of a function using the `SECURITY` clause. The `SECURITY` clause | ||
can be set to `DEFINER` or `INVOKER`. When set to `DEFINER`, the function is executed with the privileges of the | ||
user that defined the function. When set to `INVOKER`, the function is executed with the privileges of the user that | ||
invoked the function. This is useful when you want to create functions that execute with elevated privileges. | ||
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Atlas now supports defining the security level of functions in your schema. Here's an example of how you can define | ||
a function with `SECURITY DEFINER` in Atlas: | ||
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```hcl | ||
function "positive" { | ||
schema = schema.public | ||
lang = SQL | ||
arg "v" { | ||
type = integer | ||
} | ||
return = boolean | ||
as = "SELECT v > 0" | ||
// highlight-next-line | ||
security = DEFINER | ||
} | ||
``` | ||
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## Wrapping Up | ||
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That's all for this release! We hope you try out (and enjoy) all of these new features and find them useful. | ||
As always, we would love to hear your feedback and suggestions on our [Discord server](https://discord.com/invite/zZ6sWVg6NT). |
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