dbt-sqlserver
A Microsoft SQL Server adapter plugin for dbt
Decision gist · record as of 2026-08-14
Yes. The adapter is production-stable (Development Status 5), actively maintained with a recent release, has no known vulnerabilities, and low install friction. Choose it if you are committed to SQL Server or Azure SQL and want to use dbt's transformation framework. Verify beforehand that your target SQL Server version (2017 or newer) and Python version (3.10+) are supported, and plan for backend dependencies: either the Microsoft ODBC driver or optional mssql-python system libraries.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Microsoft ODBC Driver for SQL Server (pyodbc backend) or system libraries libltdl7, libkrb5-3, libgssapi-krb5-2 (mssql-python backend).
- Python 3.10 or newer.
- Low friction install with pure Python wheel distribution.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute this adapter freely in commercial and private projects with minimal restrictions.
last release 2026-08-11 (3 days) · last repo commit 2026-08-13 · 254 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 193,995 downloads/mo, #9,846 on PyPI
Alternatives
Verify before relying
pip install -U dbt-sqlserver
# In profiles.yml:
your_profile:
target: dev
outputs:
dev:
type: sqlserver
host: your-server
port: 1433
database: your-database
schema: dbo
user: your-user
password: your-password- Whether Azure SQL Database and Azure SQL Managed Instance work reliably in production (documented as expected to be compatible but not covered by integration tests).
- Performance characteristics and scalability limits for large-scale incremental model refreshes with safe type expansion enabled.
What it is and what it does
dbt-sqlserver is a plugin that connects the dbt data transformation framework to Microsoft SQL Server and Azure SQL services. It allows you to write dbt models, tests, and macros that run against SQL Server as your data warehouse, following dbt's standard project structure and workflow. The adapter handles SQL Server-specific syntax, schema management, and connection pooling through either pyodbc (the default ODBC-based backend) or an optional mssql-python backend that avoids ODBC driver dependencies.
The adapter supports SQL Server 2017 through 2025 and is tested against Python 3.11, 3.12, and 3.13. It includes features like safe type expansion for incremental models, configurable schema concatenation behavior, transaction control options, and XACT_ABORT handling to prevent partial batch commits on errors. Installation is straightforward via pip, though you must separately install the appropriate SQL Server driver or system libraries depending on which backend you choose.
Use it for
- Build and test data transformation pipelines on SQL Server without writing raw T-SQL, using dbt's model and test abstractions.
- Migrate dbt projects from other data warehouses to SQL Server or Azure SQL by swapping the adapter and adjusting SQL Server-specific configurations.
- Automate incremental table refreshes with safe column type expansion, avoiding manual schema migrations during model evolution.
- Integrate SQL Server as a dbt-compatible warehouse in multi-warehouse analytics stacks or data mesh architectures.
- Run dbt tests and data quality checks against SQL Server tables as part of a CI/CD pipeline.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The adapter is production-stable (Development Status 5), actively maintained with a recent release, has no known vulnerabilities, and low install friction. Choose it if you are committed to SQL Server or Azure SQL and want to use dbt's transformation framework. Verify beforehand that your target SQL Server version (2017 or newer) and Python version (3.10+) are supported, and plan for backend dependencies: either the Microsoft ODBC driver or optional mssql-python system libraries.
Install
dbt-sqlserver on PyPI
Before you install
Low friction install with pure Python wheel distribution. Active maintenance with a release 3 days old. Requires either pyodbc with Microsoft ODBC driver or optional mssql-python backend; system library dependencies vary by backend choice and OS.
Requires Microsoft ODBC Driver for SQL Server (pyodbc backend) or system libraries libltdl7, libkrb5-3, libgssapi-krb5-2 (mssql-python backend). Python 3.10 or newer.
License in practice
MIT license is permissive; you may use, modify, and distribute this adapter freely in commercial and private projects with minimal restrictions.
Quickstart
pip install -U dbt-sqlserver
# In profiles.yml:
your_profile:
target: dev
outputs:
dev:
type: sqlserver
host: your-server
port: 1433
database: your-database
schema: dbo
user: your-user
password: your-passwordVerify before relying
- Whether Azure SQL Database and Azure SQL Managed Instance work reliably in production (documented as expected to be compatible but not covered by integration tests).
- Performance characteristics and scalability limits for large-scale incremental model refreshes with safe type expansion enabled.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesdbt-coredbt-commondbt-adapterspyodbc |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 193,995 / month, #9,846 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/StableLicense :: OSI Approved :: MIT LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: dbt_sqlserver-1.11.1-py3-none-any.whl
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