dbt-core
With dbt, data analysts and engineers can build analytics the way engineers build applications.
Decision gist · record as of 2026-08-14
Yes. dbt-core is production-stable, actively maintained, and widely adopted in the data engineering community. Low install friction, permissive licensing, and no known vulnerabilities make it a safe choice. Install it if you need to build SQL-based data transformations with testing and documentation; you will also need to install a warehouse-specific adapter (dbt-postgres, dbt-snowflake, etc.) to actually connect to your data warehouse.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- dbt-core is a CLI-first tool; typical usage involves dbt projects on disk and a configured data warehouse adapter (not included in dbt-core itself).
- Low install friction with a pure-Python wheel.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for enterprise and proprietary projects.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 13,638 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 113,685,611 downloads/mo, #313 on PyPI
Alternatives
Verify before relying
pip install dbt-core
from dbt.cli.main import dbt_debug
from click.testing import CliRunner
runner = CliRunner()
result = runner.invoke(dbt_debug, [])- Whether dbt-core alone can connect to and transform data without installing a separate adapter package (e.g., dbt-postgres, dbt-snowflake).
- Specific data warehouse systems supported by dbt-core versus those requiring adapter installation.
- Performance characteristics or scalability limits for large transformation projects.
What it is and what it does
dbt-core is the open-source framework for analytics engineering that lets data analysts and engineers write SQL select statements (called models) to transform data in a warehouse, then automatically compiles them into tables and views. It treats data transformation like software engineering: models can reference each other, dependencies are managed explicitly, and the framework provides testing and documentation generation out of the box.
The package handles the orchestration layer—parsing your project, resolving model dependencies, running tests, and tracking lineage—while delegating actual warehouse execution to adapter packages. It's designed for teams building reproducible, version-controlled analytics pipelines and is widely used in modern data stacks. Installation is straightforward, maintenance is active, and it runs on current Python versions.
Use it for
- Build modular SQL transformation pipelines where models reference each other and dependencies are explicit and visualized.
- Add data quality tests to your transformation logic and fail pipelines when data doesn't meet expectations.
- Generate and maintain documentation of your data models and their lineage automatically as part of your project.
- Version-control your analytics code and collaborate on data transformations using Git workflows.
- Integrate data transformations into CI/CD pipelines to test and deploy changes to production warehouses.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
dbt-core is production-stable, actively maintained, and widely adopted in the data engineering community. Low install friction, permissive licensing, and no known vulnerabilities make it a safe choice. Install it if you need to build SQL-based data transformations with testing and documentation; you will also need to install a warehouse-specific adapter (dbt-postgres, dbt-snowflake, etc.) to actually connect to your data warehouse.
Install
dbt-core on PyPI
Before you install
Low install friction with a pure-Python wheel. Active maintenance—last commit 2026-08-14, release 2 days old. Supports Python 3.10 through 3.14, including PyPy. Substantial dependency footprint (25 runtime packages) is typical for a data platform and poses no unusual friction.
Requires Python 3.10 or later. dbt-core is a CLI-first tool; typical usage involves dbt projects on disk and a configured data warehouse adapter (not included in dbt-core itself).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions, making it suitable for enterprise and proprietary projects.
Quickstart
pip install dbt-core
from dbt.cli.main import dbt_debug
from click.testing import CliRunner
runner = CliRunner()
result = runner.invoke(dbt_debug, [])Verify before relying
- Whether dbt-core alone can connect to and transform data without installing a separate adapter package (e.g., dbt-postgres, dbt-snowflake).
- Specific data warehouse systems supported by dbt-core versus those requiring adapter installation.
- Performance characteristics or scalability limits for large transformation projects.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 25 packagesagateclickdaffdbt-adaptersdbt-commondbt-core-experimental-parserdbt-extractordbt-protosjinja2jsonschemamashumarometricflownetworkxopentelemetry-apipackagingpathspecprotobufpydanticpython-dotenvpytzpyyamlrequestssnowplow-trackersqlparsetyping-extensions |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 113,685,611 / month, #313 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPy |
Evidence: dbt_core-1.12.2-py3-none-any.whl
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See also dbt · dbt-bigquery · dbt-core-experimental-parser · dbt-core-interface · dbt-oracle · elementary-data · sqlmesh · dbt-exasol · dbt-postgres · dbt-spark