We recently shipped a new feature in Atlas that enables developers to quickly create ERD (Entity Relationship Diagram) visualizations of their database schemas. Today, I want to show how this feature can be used in tandem with one of Atlas's core capabilities - "Schema Loaders" - to produce visualizations of GORM models.

But first, let's introduce the different characters in this story:

• Atlas - an open-source tool for managing database schemas.
• GORM - one of the most popular ORMs for Go.
• ERD - a diagram that shows the relationships between entities in a database. (we'll see an example in a minute)
• Schema Loaders - a feature in Atlas that allows users to load their database schemas from different sources.

In this blog post, we will create a toy GORM application, and show how you can use Atlas to visualize the database schema that GORM generates for you.

It's been just over two months since our last version announcement and today I'm super excited to share with you our latest release, v0.13, which includes some long-anticipated additions to Atlas:

• Atlas and Atlas Community Editions - we are making a change in the way Atlas is distributed. Starting today, we are making many of the features previously available only in the commercial version of Atlas available to everyone for free. More on this below.

• Support for SQL Views - SQL Views are virtual tables in a database created by a query and stored in the database. Starting today, you can manage views in your database using the same Atlas workflows you use for tables, indexes, foreign keys, etc.

• Microsoft SQL Server Driver Beta - Over the last few months, we have been working on a driver for MS-SQL with some of our enterprise design partners and are happy to make it available to you as a beta.

• Built-in schema visualization - Over the past year we released some tools to help developers visualize their database schemas using Entity Relationship Diagrams (ERDs). Starting today, you can use the atlas schema inspect --visualize command to create database ERDs directly from the command line.

• GitHub Action for Deployments - We recently received a request from the community to add a GitHub Action to streamline applying migrations directly from GitHub workflows. We thought this was a great idea and are happy to introduce ariga/atlas-deploy-action which you can use to deploy your migrations today.

• Type checking for schema files - As part of our continuous effort to make the experience of working with Atlas as smooth as possible, we are excited to ship a new engine for running type checks on your schema files.

This release is extra-packed with new features and improvements, so let's dive in!

Introduction​

When we started building Atlas a couple of years ago, we noticed that there was a substantial gap between what was then considered state-of-the-art in managing database schemas and the recent strides from Infrastructure-as-Code (IaC) to managing cloud infrastructure.

In this post, we review that gap and show how Atlas – along with its Terraform provider – can bridge the two domains.

As an aside, I usually try to keep blog posts practical and to the point, but occasionally think it’s worth it to zoom out and explain the grander ideas behind what we do.

If you’re looking for a quick and practical explanation of working with Atlas and Terraform, I recommend this YouTube video.

Introduction​

The Atlas Kubernetes Operator is a Kubernetes operator that enables you to manage your database schemas natively from your Kubernetes cluster. By exposing custom resource definitions (CRD) the operator extends the Kubernetes API to support database schema management.

In a previous blog post we demonstrated how to use the Atlas Operator for the declarative (state-based) workflow in which you define the desired state of your database schema in a Kubernetes manifest and the operator takes care of the rest.

State vs. versioned based migrations is a common and unresolved debate in the database schema management world, and we built Atlas to support both from the get-go.

Today, we are happy to announce v0.2.0 of the Atlas Kubernetes Operator which adds support support for the versioned migration workflow.

In this blog post we will demonstrate how to use the Atlas Operator this new workflow.

Introduction​

Today, I'm happy to share with you one of the most exciting features we've added to Atlas since its inception: "External Schemas".

Atlas is a modern tool for managing your database schema. It allows you to inspect, plan, lint and execute schema changes to your database. It is designed to be used by developers, DBAs and DevOps engineers alike.

Schema-as-Code​

Atlas is built around the concept of database "Schema-as-Code", which means that you define the desired schema of your database in a declarative way, and Atlas takes care of planning and executing the necessary migrations to get your database to the desired state. The goal of this approach is to let organizations build a single source of truth for complex data topologies, and to make it easy to collaborate on schema changes.

Schema Loaders​

To achieve this goal, Atlas provides support for "Schema Loaders" which are different mechanisms for loading the desired state of your database schema into Atlas. Until today, Atlas supported a few ways to load your schema:

• Using Atlas DDL - an HCL based configuration language for defining database schemas.
• Using Plain SQL - a simple way to define your schema using plain SQL files (CREATE TABLE statements, etc.)
• From an existing database - Atlas can connect to your database and load the schema from it.
• The Ent ORM - Atlas can load the schema of your Ent project.

Today, we are adding support for "External Schemas", which means that you can now import the desired database schema from any ORM or other tool into Atlas, and use it to automatically plan migrations and execute them for you.

Today we are happy to announce that Atlas Cloud, our cloud offering, has achieved SOC2 compliance. This is a big milestone for us, which shows our determination to providing solid infrastructure for our users and customers.

SOC2 is a security and compliance standard that helps organizations demonstrate their ability to protect customer data and ensure the availability of their services. It’s like an independent third-party audit that evaluates how well a company follows industry-standard security practices, covering areas such as availability, processing integrity, confidentiality, and privacy.

Achieving SOC2 compliance requires a significant investment in time, effort, and resources, so you may be wondering why we decided to pursue this goal so early in the life of our product. The knee-jerk response of any seasoned engineer to large and long infrastructure projects should is:

YAGNI. You ain’t gonna need it.

Today, we are delighted to share that Ariga (the company behind Atlas) has raised 18M$ in total from Tiger Global and TLV Partners to build our vision for the future of how organizations work with their databases.

This is an important milestone for us as it provides us with the resources we need to keep growing our open-source communities and build the products we envision for the industry. I want to take this opportunity to reflect on the work we've done in the past two+ years, and where we are going as a company.

Background​

Databases play a crucial role in driving a company's success. From the outset, companies invest time in selecting a suitable database for building their product, modeling its schema, and building their application on top of it. As companies grow, they face challenges in performance, security, privacy, and more. Databases remain a vital component, accompanying businesses from the earliest stages and throughout their entire journey.

Ariga was founded after a decade of experience in building database infrastructure, and dev tooling frameworks. Our focus in the last two years has been on three fundamental pillars:

• Pioneering the “Schema-as-Code” concept within the industry
• Building an innovative database change management platform
• Open sourcing a versatile framework for developing data-driven server applications

I want to elaborate on these pillars and describe how they shaped our mission statement as an engineering team and a company.

It has been two months since we announced the Community Preview Plan for Atlas Cloud, and today I am thrilled to announce the next batch of features that we are releasing to open-source and to Atlas Cloud:

In summary, version v0.12 includes a few major features that are explained in detail below:

1. We have added support for importing and running migration linting on GitHub PRs for external migration formats, such as Flyway and golang-migrate.
2. Atlas now supports reading your migration directory directly from your Atlas Cloud account. This eliminates the need for users to build their Docker images with the directory content and makes running schema migrations in production much easier.
3. By connecting Atlas CLI to Atlas Cloud, migration runs will be recorded in the cloud account, making it easier to monitor and troubleshoot executed migrations.
4. A new Slack integration is now available for Community Plan accounts. Organizations that connect their migration directories to the cloud can receive notifications to Slack channels when the schemas are updated or deployed, among other events.
5. A new look has been given to the CI report page. It will be enhanced with additional features in the next version.

Having a visual representation of your data model can be helpful as it allows for easier comprehension of complex data structures, and enables developers to better understand and collaborate on the data model of the application they are building.

Entity relationship diagrams (ERDs) are a common way to visualize data models, by showing how data is stored in the database. ERDs are graphical representations of the entities, their attributes, and the way these entities are related to each other.

Today we are happy to announce the release of DjangoViz, a new tool for automatically creating ERDs from Django data models.

Introduction​

Atlas supports many ways to describe database schemas. Using Schema Loaders, Atlas gives users the flexibility to define schemas using plain SQL, a connection to another database or using Atlas HCL.

What is Atlas HCL?​