dbt-exasol

What it is and what it does

dbt-exasol bridges dbt-core and Exasol, allowing data engineers to write and orchestrate SQL transformations on Exasol warehouses using dbt's familiar project structure, testing, and documentation tools. It implements most dbt-core 1.12 features including incremental models with microbatch strategy, SQL and Python user-defined functions, snapshots, unit testing, and grants management. Some platform limitations exist: Python models, materialized views, and native zero-copy clones are not supported due to Exasol's architecture; microbatch concurrency runs sequentially because Exasol uses optimistic transaction-conflict detection at table granularity.

The adapter is marked production-ready and actively maintained. It depends on dbt-core, dbt-adapters, dbt-core-experimental-parser, protobuf, and pyexasol for connectivity. Installation is straightforward via pip, and configuration uses a standard dbt profiles.yml with Exasol connection parameters (DSN, user, password, schema). It supports Python 3.11–3.14 and Exasol versions 7.x, 8.x, and ≥2025.x.

Use it for:

• Build and test SQL transformation pipelines on Exasol using dbt's project structure and version control.
• Implement incremental models with microbatch strategy to efficiently update large Exasol tables.
• Define and test SQL and Python user-defined functions (UDFs/UDAFs) as dbt models.
• Create and maintain slowly-changing-dimension snapshots with hard_deletes and dbt_valid_to_current support.
• Generate and enforce data contracts through dbt unit tests and column-level documentation.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

dbt-exasol is a dbt adapter that enables data transformation workflows on Exasol warehouses using dbt's SQL and Python capabilities.

Yes, with conditions. Install if you use Exasol as your warehouse and want dbt's transformation and testing framework. The adapter is production-ready, actively maintained, and covers most dbt-core 1.12 features. However, be aware of platform limitations: Python models, materialized views, and native zero-copy clones are not supported. The GPL-3.0-or-later license requires any derivative work to remain open-source, which may conflict with proprietary projects.

Install

dbt-exasol on PyPI

pip install dbt-exasol

uv add dbt-exasol

poetry add dbt-exasol

Installing dbt-exasol

Before you install

Low friction installation with a pure-Python wheel. Actively maintained with a recent release (20 days old). Depends on dbt-core, dbt-adapters, and pyexasol; all are standard data-stack libraries. Supports Python 3.11–3.14.

License in practice

GPL-3.0-or-later (copyleft). Any derivative work or distribution must also be licensed under GPL-3.0-or-later; proprietary or closed-source projects cannot use this adapter without relicensing.

Quickstart

pip install dbt-exasol

# In profiles.yml:
dbt-exasol:
  target: dev
  outputs:
    dev:
      type: exasol
      dsn: HOST:PORT
      user: USERNAME
      password: PASSWORD
      dbname: db
      schema: SCHEMA

# Then:
dbt run

Requires an Exasol instance (7.x, 8.x, or ≥2025.x) and a valid connection DSN, user, and password. Python 3.11 or later required.

Verify before relying

• Whether the adapter's feature parity with dbt-core 1.12 (as documented in the description) is maintained across all minor releases.
• Performance characteristics and connection pooling behavior under concurrent workloads.
• Whether OpenID/SaaS authentication (mentioned as optional) is fully tested and production-ready.

Package facts

Evidence: dbt_exasol-1.12.0-py3-none-any.whl

Tags

More Database packages