Trust Your Data. Know Why You Can't.

Open-source data contract enforcement for modern data teams.
Define contracts in YAML. Sync to dbt. Validate in CI. Block bad data before it reaches production.

Official ODCS Vendor — Listed on the Bitol registry alongside Data Contract CLI, Data Caterer, and DQC.ai.

The problem

89% of data teams report pain points with data modeling and ownership. Data contracts are the solution — but the tooling is fragmented:

• dbt tests → SQL only, no formal contract, no pre-ingestion validation
• Great Expectations → verbose Python, steep learning curve, no standard format
• Soda → good YAML checks, but no CI/CD gate, no stakeholder reporting, no ODCS
• Data Contract CLI → ODCS compatible, but no dbt sync, no scoring, no CI gate

Quick start

pip install datavow
Initialize a project
datavow init my-project
Define a contract
datavow define contracts/orders.yaml
Validate data against contracts
datavow validate contracts/orders.yaml --source data/orders.csv
Generate an HTML report
datavow report contracts/orders.yaml --source data/orders.csv --format html
Run in CI mode (exit code 1 on critical violations)
datavow ci contracts/ --source data/

Key features

YAML-first contracts (ODCS v3.1 native)

Define schemas, quality rules, and SLAs in readable YAML. DataVow supports both its own format and native ODCS v3.1 contracts — auto-detected, no config needed.

apiVersion: datavow/v1
kind: DataContract
metadata:
  name: orders
  version: 1.0.0
  owner: data-team@company.com
  domain: sales
schema:   type: table   fields:     - name: order_id       type: integer       required: true       unique: true     - name: customer_email       type: string       required: true       pii: true
quality:   rules:     - name: nonegativetotals       type: sql       query: "SELECT COUNT(*) FROM {table} WHERE total_amount < 0"       threshold: 0       severity: CRITICAL

datavow dbt sync — the killer feature

One command generates dbt-native tests from your contracts. Works on every dbt adapter — no connector needed.

# Generate dbt tests from contracts
datavow dbt sync contracts/ --dbt-project-dir .
Generates generic + singular tests from your contracts
All tagged datavow for easy filtering

Airflow Integration

Run data contract validation as an Airflow task with DataVowOperator.

pip install datavow[airflow]   # requires apache-airflow>=2.7

Standalone DAG:

from datavow.airflow.operators import DataVowOperator
validate = DataVowOperator(     taskid="validateorders",     c,     data_path="/data/bronze/orders.parquet",     ,       # fail | warn | skip     fail_on="strained",     # strained (<95) | broken (<80) | shattered (<50)     report_format="html",     report_path="/data/reports/orders.html", )

Lakecast YAML (ADR-013):

tasks:
  - name: validate_orders
    type: datavow
    contract: contracts/orders.yaml
    source: "{{ params.bronze_path }}/orders.parquet"
    fail_on: broken

| XCom Key | Description | |---|---| | vow_score | Integer 0–100 | | vow_verdict | Vow Kept / Strained / Broken / Shattered | | violations_critical | Count of CRITICAL failures | | violations_warning | Count of WARNING failures | | violations_info | Count of INFO failures | | contract_name | Contract name from YAML | | report_path | Path to generated report (if any) |

K8s executor: Imports are lazy — the scheduler node does not need datavow installed.

Vow Score — every validation renders a verdict

Vow Score = 100 - (20 × CRITICAL + 5 × WARNING + 1 × INFO)
95-100  ✅ Vow Kept      — fully compliant, ship it   80-94   ⚠️ Vow Strained  — action needed   50-79   🔧 Vow Broken    — blocking issues    0-49   ❌ Vow Shattered  — critical violations

CI pipeline gating

Block bad data automatically. No manual intervention.

GitHub Action (Marketplace):

- uses: ludovicschmetz-stack/datavow-action@v1
  with:
    contracts: contracts/
    source: data/
    fail-on: critical
    comment-on-pr: "true"

dbt on-run-end hook (datavow-dbt):

# dbt_project.yml
on-run-end:
  - "{{ datavow_summary() }}"
vars:   datavowfailon: broken  # block pipeline on Vow Broken or worse

ODCS v3.1 — validate against the official standard

# Validate a contract against the ODCS v3.1 JSON Schema
datavow odcs check contracts/orders.yaml
Convert ODCS native → DataVow format
datavow odcs convert contracts/orders-odcs.yaml -o contracts/orders.yaml

DataVow bundles the official ODCS v3.1.0 JSON Schema (2928 lines, Draft 2019-09). No other CLI tool does this.

Full command reference

| Command | Description | |---|---| | datavow init | Initialize project with config and example contract | | datavow define | Create or edit a data contract interactively | | datavow validate | Validate data against contracts | | datavow report | Generate HTML or Markdown reports | | datavow ci | CI mode — validate + exit code 0/1 | | datavow dbt generate | Auto-generate contracts from dbt manifest | | datavow dbt validate | Validate against dbt warehouse (via profiles.yml) | | datavow dbt sync | Generate dbt tests from contracts | | datavow dbt ci | Full pipeline: sync → dbt test → Vow Score | | datavow odcs check | Validate contract against ODCS v3.1 JSON Schema | | datavow odcs convert | Convert ODCS native → DataVow format |

Data sources

DataVow validates files and databases via DuckDB:

| Source | How | |---|---| | CSV, Parquet, JSON, TSV | Direct file validation | | PostgreSQL | datavow validate --source postgresql://... | | DuckDB | datavow validate --source path/to/db.duckdb |

For cloud warehouses (Snowflake, BigQuery, Redshift, Databricks), use datavow dbt sync — it generates dbt-native tests that run on your existing dbt adapter. No extra connector needed.

Built for your whole team

| Persona | Uses | Gets | |---|---|---| | Data Engineer | datavow ci in pipeline | Automated quality gate | | Analytics Engineer | datavow dbt sync | One source of truth, zero test duplication | | Domain Data Owner | YAML contracts in git | Versioned, reviewable data agreements | | Data Governance | HTML reports | Conformity view across domains | | Tech Lead | CI gate + Vow Score | No pipeline in prod without a contract | | Freelance / Consultant | datavow report | Quality proof attached to every delivery |

Architecture

┌─────────────┐    ┌──────────────┐    ┌─────────────┐
│  YAML       │    │   DataVow    │    │   Outputs   │
│  Contracts  │───▶│   Engine     │───▶│             │
│  (ODCS/DV)  │    │   (DuckDB)   │    │  ✅ Score   │
└─────────────┘    └──────┬───────┘    │  📊 Report  │
                          │            │  🚦 Exit 1  │
              ┌───────────┼──────┐     └─────────────┘
              ▼           ▼      ▼
          CSV/Parquet  PostgreSQL  dbt

Ecosystem

| Package | Description | Version | |---|---|---| | datavow | CLI — define, validate, report, CI | v0.3.0 | | datavow-action | GitHub Action — CI gate | v1.0.0 | | datavow-dbt | dbt package — on-run-end Vow Score | v1.0.0 |

Contributing

Contributions are welcome! See CONTRIBUTING.md for guidelines.

# Development setup
git clone https://github.com/ludovicschmetz-stack/datavow.git
cd datavow
python -m venv .venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest  # 137 tests

License

Apache 2.0 — free forever. Use it, fork it, ship it.

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