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Getting Started

Welcome to dbdeux. The modern, cloud-native IDE built for data teams who want to move fast with dbt.

What is dbdeux?​

dbdeux is a complete development platform for dbt projects. It replaces the fragmented workflow of local editors, terminal sessions, and manual deploys with a single, integrated experience:

What you getWhat it replaces
Cloud IDE with SQL/YAML/Jinja editing, per-file run buttons, and compiled SQL tabVS Code + dbt extensions + local Python environment
Worksheets for ad-hoc SQL with results grid, charts, and exportSeparate SQL clients (DataGrip, DBeaver, etc.)
Database Explorer with drag-and-drop schema browsingManual INFORMATION_SCHEMA queries
Visual DAG Explorer with column-level lineageManual dbt docs generate + static site
Slimmer CI with AI code review, metric gate, schema diffs, and state comparisonCustom CI pipelines + manual dbt Cloud CI setup
One-click runs against your warehouseTerminal + manual dbt run commands
Schema Diff showing exact changes between runsManual schema comparison scripts
Automated scheduling with dependency chainsExternal orchestrators (Airflow, Dagster, etc.)
Built-in testing with visual resultsTerminal test output + manual review
Team collaboration with Git workflows (GitHub, GitLab, Azure DevOps, Bitbucket)Separate Git client + code review tools
Atlas AI Co-pilot grounded in your schema and modelsSeparate AI tools with no context
Atlas Metrics with catalog browser, live SQL preview, and metric diffsSpreadsheets, LookML, or no shared metric layer
Organizations with AI budgets, member roles, and instant switchingManual team management
Multi-version dbt (Core 1.8, 1.10, Fusion) selectable per projectPinned to a single dbt version
Connection Tags with environment classification, production guardrail, and org-wide filteringManual naming conventions
Data Products with governance, SLA tiers, and reference validationSpreadsheets or tribal knowledge about data assets
Share Links for external catalog sharing without loginScreenshots and exported CSVs
Atlas Catalog with project overview, zoomable DAG graph, all eight node types, coverage scoring, and column lineagedbt docs serve + manual coverage audits
Shared Workspaces with private/team/org visibility and project copyAll projects visible to everyone
Audit Log with full action historyCustom logging solutions
Notifications via Slack, email, PagerDuty, webhooksCustom alerting scripts
Post-Run Actions triggering Power BI refresh and API endpoints after buildsCustom scripts and manual triggers
Integrations with a central credential store for Power BI, API Endpoints, and PagerDutySecrets duplicated across pipelines
Sandbox Environments with per-developer schema isolationManual schema naming conventions
Service Accounts & API with scoped tokens to trigger jobs programmaticallyCustom auth wrappers or shared credentials

Get Started in 5 Minutes​

Step 1: Sign Up​

Sign up through dbdeux.com and access dbdeux from your dashboard. You can sign in with:

  • Google Workspace
  • Email and password

Your 14-day free trial includes all features with no credit card required.

Step 2: Connect Your Warehouse​

Add your data warehouse credentials so dbdeux can execute queries on your behalf:

  1. Go to Settings → Connections
  2. Click + Add Connection
  3. Choose your warehouse (Snowflake, BigQuery, Redshift, Athena, Databricks, PostgreSQL, MotherDuck, Microsoft Fabric, Azure Synapse, Fabric Lakehouse, or StarRocks)
  4. Enter your credentials
  5. Click Test Connection to verify

All credentials are encrypted and never stored in plain text. If a teammate has already set up a connection, ask them for a Connection Template token to pre-fill your config instantly. → Detailed guide

Step 3: Import Your dbt Project​

Point dbdeux at your existing dbt project repository:

  1. Go to Projects → New Project
  2. Connect your Git provider (GitHub, GitLab, Azure DevOps, or Bitbucket)
  3. Search and select the repository containing your dbt project
  4. Choose the branch and dbt project subdirectory (if applicable)
  5. Assign a connection and environment

dbdeux reads your dbt_project.yml and packages.yml automatically. An animated progress indicator shows the clone status while your project is being set up.

Step 4: Start Developing​

A first-run onboarding checklist guides you through connecting your warehouse, importing a project, and running your first model. Once complete, open any model in the IDE, make a change, and click Run to see results instantly.

The first time you sign in, an org-aware guided tour highlights the key areas of the app (environments, databases, catalog, and jobs) with a spotlight walkthrough so you know where everything lives. You can dismiss it at any time, and it will not reappear on your next visit.

Explore the Platform​

Now that you are set up, explore what dbdeux can do:

Build​

  • Cloud IDE: Write and edit dbt models in a powerful browser-based editor
  • Worksheets: Run ad-hoc SQL queries and explore data interactively
  • Database Explorer: Browse your warehouse schema with drag-and-drop
  • DAG Explorer: Visualize your project's lineage interactively
  • Version Control: Branch, commit, and collaborate with Git
  • Git Provider Tokens: Required scopes and setup for GitHub, GitLab, Azure DevOps, Bitbucket
  • Atlas AI Co-pilot: AI assistant grounded in your schema and models
  • Atlas Metrics: Shared metric catalog with live SQL and branch diffs
  • Data Products: Governed data product catalog with SLAs and ownership
  • Share Links: Share your metric catalog externally without requiring a login
  • Atlas Catalog: Server-indexed documentation browser with project overview, zoomable DAG graph, all eight node types, and coverage scoring
  • Shared Workspaces: Organize projects into private, team, or org-wide workspaces
  • Connecting Your Warehouse: Setup guide including shareable Connection Templates and Connection Tags

Test​

  • Slimmer CI: Automated PR validation with AI code review and schema diffs
  • Data Testing: Validate data quality at every step
  • Schema Diff: See schema changes between runs
  • Environments: Isolate dev, staging, and production with per-environment dbt variables, sandbox schemas, and extended attributes

Deploy​

  • Job Scheduling: Automate runs on any schedule with post-run actions (Power BI refresh, API endpoints)
  • Integrations: Central credential store for Power BI, API Endpoints, and PagerDuty
  • Notifications: Get alerted when things need attention via Slack, email, PagerDuty, or webhooks
  • Multi-Warehouse: Connect to any major data platform

Govern​

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