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SQLBuild

The refactorable warehouse. Verify early, test properly, and refactor safely.

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Change your warehouse as often as your code. SQLBuild brings compile-time checks, end-to-end tests and safe renames to your SQL, so change stops being risky. It is a free, open-source framework for SQL and Python data pipelines, and it keeps its state in append-only tables in your own warehouse: no external state database, no manifest files and no paid tier.

Its compiler and planner run in Rust. Warehouse execution and extensions use Python.

Moving and renaming an incremental model with sqb mv: sqb plan migrates the existing table instead of rebuilding it

Move an incremental model to a new folder and name with sqb mv, and sqb plan migrates its table instead of rebuilding it.

Quick start

pip install sqlbuild
sqb playground waffle-shop
cd waffle-shop
sqb plan
sqb build
sqb test

The playground runs on local DuckDB, with no warehouse credentials.

What it does

Catch mistakes before anything runs

  • Compile-time checks. SQLBuild resolves references, validates SQL, infers column types, checks contracts and computes column lineage, all offline. A typo'd column fails in seconds, not halfway through a warehouse run.
  • Your conventions as rules. Built-in and custom Python rules turn review comments into compile errors: for example, marts can't read sources directly, or every final model declares its key.

Prove it works

  • Tests across models. SQL tests mock the sources and check the result through every model in between, with macros as test helpers. Macro, UDF and table-function tests are built in.
  • End-to-end scenarios. Build the real graph against fixture data, capture fixtures from the warehouse, and replay them locally on DuckDB in CI. See scenarios.
  • Audits and diffs. Audits run before data reaches the target table, and data diffs compare dev against prod or any query.

Change it without rebuilding everything

  • Renames keep their history. sqb rename and sqb mv update every reference, and the next build migrates the existing table instead of rebuilding it. The old name keeps working through a compatibility view. sqb rename <model>.<column> renames an incremental model's column in place.
  • Replay on change. When a model's SQL changes, choose how far back to reprocess, from only the new data to the last 14 days to a full rebuild, with replay_on_change.
  • Macros don't have to be global. Keep macros, enums and constants next to the models that use them, and preview what a move would break with sqb scope. See declaration scopes.
  • Tidy up safely. The janitor archives stale tables before anything is deleted.

Find out what happened

  • Every run is recorded. Recall keeps each command's statements, SQL, audit results and exact output. Agents and people query it with SQL through sqb recall, then check live state in the warehouse with the same command. History stays in a SQLite file in the project, or in ClickHouse for a team.

Ingestion with Python loaders, and Python tasks, assets and checks, run in the same graph as your SQL models. See the docs for everything else.

In the terminal

Each demo is real output from the example projects in website/examples, running on local DuckDB.

A renamed column breaks the contract

daily_revenue declares contract enforced. Renaming waffles_sold to units_sold in the SELECT fails at compile time, before anything reaches the warehouse.

sqb compile fails because units_sold is not in the enforced contract and the declared waffles_sold column is missing

Both sides are reported: the new column isn't in the contract, and the declared one is gone.

Your own conventions as compile errors

Rules are Python functions in your project. This one, from rules/layers.py, says marts must read sources through staging:

from sqlbuild.rules import Finding, Model, RuleContext, rule


@rule(
    code="XSQBRARCH001",
    message="Marts must read sources through staging",
    remediation="Reference a staging model with __ref() instead.",
)
def marts_use_staging(*, model: Model, ctx: RuleContext) -> list[Finding]:
    layer = ctx.project.tree.relative_parts(path=model.path, under="models")[0]
    sql = ctx.sql.for_model(model).authored.source
    if layer != "marts" or "__source(" not in sql:
        return []
    line = sql[: sql.index("__source(")].count("\n") + 1
    return [ctx.finding(subject=model, line=line)]

A mart that reads __source("raw__payments") directly now fails, and so does the unit test that has no mock for it:

sqb compile reports the custom rule XSQBRARCH001 on the line that reads a raw source, and a unit test with no mock for that source

See rules.

See what a move would break

sqb scope --as-path previews moving a model before you move it.

sqb scope previews moving daily_revenue: the enum and macro it uses would be lost, so both usages are invalidated

Look at Lost and Invalidated usages: the model uses an enum and a macro that are private to models/marts, so moving it would break both.

Example

A model is a SQL file with a MODEL() header and a SELECT:

MODEL (
  description "One row per order",
  materialized table,
  columns (
    order_id (audits [not_null, unique]),
  ),
  tags [marts],
);

SELECT
  o.order_id,
  o.customer_id,
  p.amount_cents AS total_cents,
  @py.cents_to_dollars("p.amount_cents") AS total_dollars
FROM __ref("stg_orders") o
JOIN __ref("stg_payments") p USING (order_id)

Python macros are plain functions that return SQL, kept next to the models that use them; SQL macros in macros/sql/ cover logic-free fragments with typed, checked arguments:

# models/marts/_sqlbuild/_macros/python/currency.py
def cents_to_dollars(column: str) -> str:
    """Convert a cents integer column to a dollars decimal with two decimal places."""
    return f"ROUND(({column}) / 100.0, 2)"

A test mocks the sources and asserts on the model, resolving every model in between from its real SQL:

TEST();

WITH
__source__raw__orders AS (
  SELECT
    1 AS id,
    100 AS customer_id,
    2 AS waffle_type_id,
    3 AS quantity,
    CAST('2026-04-01 10:00:00' AS TIMESTAMP) AS ordered_at,
    'completed' AS status
),
__source__raw__payments AS (
  SELECT
    10 AS id,
    1 AS order_id,
    1500 AS amount_cents,
    'credit_card' AS payment_method,
    CAST('2026-04-01 10:05:00' AS TIMESTAMP) AS paid_at,
    'success' AS status
),
__expected__fact_orders AS (
  SELECT 1 AS order_id, 100 AS customer_id, 1500 AS total_cents, 15.00 AS total_dollars
)

Warehouses

Warehouse Status
Snowflake Supported
DuckDB Supported
MotherDuck Supported
PostgreSQL Supported
BigQuery Beta
Databricks Beta
SQL Server Beta

Snowflake is the main target. Beta adapters build, test and plan, but have had less production use so far. See adapters.

Free and independent

SQLBuild is Apache 2.0 and will stay free: no paid tier, no commercial edition, and no feature held back for one. Its state lives in your warehouse, next to your data. See the roadmap for what's next.

Contributing

Contributions are welcome. See CONTRIBUTING.md.

License

SQLBuild is licensed under the Apache License 2.0.

Metadata

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