dbt Core | Support by cloudimg

This is a repackaged open source software product wherein additional charges apply for cloudimg support services.

dbt Core is the open source data transformation framework that lets analytics engineers build, test, and document data models in plain SQL, applying software engineering best practices to the transform step of your ELT pipeline. This AMI delivers dbt Core fully installed with the DuckDB adapter and a working sample project, so you can SSH in and run a complete transform-test-document workflow immediately - no external data warehouse, no credentials, no setup.

Installing dbt Core manually means resolving Python dependencies, configuring virtual environments, setting up adapters, writing profiles, and troubleshooting version conflicts - a process that can take hours. This image eliminates that friction entirely. The virtual environment, DuckDB adapter, system-path wrapper, sample project, and profile are preconfigured and tested as a unit. Your first dbt build completes on first login rather than after a lengthy setup cycle.

The DuckDB adapter ships preconfigured to materialise models into a local DuckDB database file on a dedicated, independently resizable data disk. The entire toolchain works with no Snowflake, BigQuery, or Redshift account. Run dbt seed, dbt run, dbt test, dbt build, and dbt docs generate the moment you log in and watch real tables and views appear in the local warehouse. The dedicated data disk means your transformed data persists independently of the compute instance and can be resized without reprovisioning.

A complete sample project ships read-only on the image: raw CSV seeds for customers, orders, and payments flow through staging views into a customers and orders mart, with schema and data tests on the models. Copy it, study the structure, and use it as the template for your own project, or replace it entirely.

dbt compiles your SQL models into a DAG, runs them in dependency order, materialises them as views or tables, asserts your tests, and generates a browsable documentation site with lineage graphs. Version your models in git, run them in CI, and ship trustworthy, tested data.

• SSH key-only authentication enabled; password login disabled
• Root SSH login disabled by default
• Minimal attack surface with only required packages installed
• Data disk supports EBS encryption at rest via AWS-managed or customer-managed KMS keys
• No data leaves the instance unless you configure an external warehouse connection
• OS-level firewall configured to restrict inbound traffic to SSH

• Minimum instance type: t3.micro (for evaluation); t3.small or larger recommended for production workloads
• Operating system: Linux-based AMI
• Data disk: Dedicated EBS volume (resizable); default size suitable for sample project and moderate workloads
• Included adapter: DuckDB only; additional adapters (Snowflake, BigQuery, Redshift, Postgres) can be installed into the virtual environment
• Scope: Support covers dbt Core usage, project structure, adapter configuration, and CI integration; custom macro development is outside standard support scope
• Updates: Image is periodically updated; in-place OS patching is the customer's responsibility between image updates

• A reproducible analytics engineering workstation with a pinned, ready-to-run dbt toolchain
• A CI runner image for dbt build and test pipelines
• A local development and prototyping environment using DuckDB before promoting models to a cloud warehouse
• A training and evaluation sandbox for teams adopting dbt