The data runtime for teams that ship.
No setup. No services. No stack.

One binary replaces ingestion, transformation, and orchestration.

models/staging/stg_orders.sql

-- @kind: merge
-- @unique_key: order_id
-- @incremental: updated_at
-- @constraint: order_id PRIMARY KEY
-- @audit: row_count > 0

SELECT
    order_id,
    customer_id,
    order_date,
    total_amount,
    status
FROM raw.orders

1
binary
0
infrastructure
0
dependencies
0
cloud required
0
config files needed
0
Python required

One system

You don't need a data stack anymore

Event → Data → Query

From event to queryable data in one system. No message broker. No ingestion layer. No orchestrator.

Runs Locally

Runs on one machine. No cluster. No cloud. No setup. Install, init, run.

Every Change Tracked

Every run is reproducible. Snapshots track every change. Rollback with time-travel.

Preview Before You Ship

Preview all changes before committing. See diffs, schema evolution, downstream impact — then decide.

No Connectors to Install

Call any API directly. HTTP, OAuth, pagination — all built in. No connectors to install. No Python.

Quality Built In

26 constraints block bad data. 17 audits catch regressions. Column lineage tracks every field. Schema evolves without migrations.

SQL + Scripts + Config

SQL for transforms. Starlark for connectors. YAML for config. One pipeline.

Built-in Event Collection

POST events to an embedded endpoint. Durable buffering. Exactly-once flush. No Kafka.

How it works

One command replaces your pipeline stack

You don't configure pipelines. You run them.

1. Install

curl -fsSL https://ondatra.sh/install.sh | sh

2. Write SQL

Place SQL files in models/. Add @kind, @incremental, @constraint as comments.

3. Run

ondatrasql run — DAG built, changes detected, data materialized.

See it in action

SQL, scripting, and validation — in one pipeline

SQL Model

Transform data with plain SQL. The framework handles materialization and change detection automatically.

models/staging/stg_customers.sql

-- @kind: scd2
-- @unique_key: customer_id
-- @constraint: customer_id NOT NULL
-- @constraint: email EMAIL

SELECT
    customer_id,
    name,
    email,
    tier,
    region
FROM raw.customers

Data Ingestion

Ingest from REST APIs with Starlark scripts. Built-in HTTP, OAuth, and pagination support.

models/raw/api_users.star

# @kind: merge
# @unique_key: id

resp = http.get(
    "https://api.example.com/users",
    headers={"Authorization": env.get("API_TOKEN")},
)

for user in resp.json:
    save.row(user)

Sandbox Preview

Preview every change before committing. See skips, diffs, schema evolution, and downstream propagation.

$ ondatrasql sandbox

╠═══ Execution ════════════════════════════╣
[OK] raw.customers (45ms)
[OK] staging.customers (128ms)
[OK] staging.orders (95ms)
[OK] mart.revenue (54ms)

╠═══ Summary ══════════════════════════════╣
Unchanged: 2 models
Changed:   2 models

╠═══ Changes ══════════════════════════════╣
staging.orders
  Rows: 100 → 142 (+42, +42.0%)
    + Added: 42 rows

mart.revenue
  SCHEMA EVOLUTION:
    + Added: region (VARCHAR)
  Rows: 5 → 6 (+1, +20.0%)

Get started in minutes

Download the binary, init a project, write your first model, and run it.

Read the Guide Browse Blueprints

The data runtime for teams that ship.No setup. No services. No stack.