What if I already have Databricks or Snowflake?

Great! Bauplan is built to be fully interoperable. All the tables produced with Bauplan are persisted as Iceberg tables in your S3, making them accessible to any engine and catalog that supports Iceberg. Our clients use Bauplan together with Databricks, Snowflake, Trino, AWS Athena and AWS Glue, Kafka, Sagemaker, etc.

What does Bauplan replace in my AWS data stack?

Bauplan consolidates pipeline execution and data versioning into one workflow: branch, run, validate, merge. You can keep S3 and your orchestrator; you remove a lot of cluster complexity and glue. For example, an Airflow DAG that spins up an EMR cluster, submits Spark steps, then runs an AWS Glue crawler to refresh the Glue Data Catalog before triggering downstream jobs becomes: Airflow triggers a Bauplan run on an isolated branch that writes Iceberg tables directly to S3.

How do you keep my data secure?

Your data stays in your own S3 bucket at all times. Bauplan processes it securely using either Private Link (connecting your S3 to your dedicated single-tenant environment) or entirely within your own VPC using Bring Your Own Cloud (BYOC).

Do I need to learn a new data framework or DSL?

No. Bauplan is just Python (and SQL for queries). That why your AI assistant can immediately write Bauplan code with no problem.

What does Git-for-Data mean?

Learn more at https://docs.bauplanlabs.com/en/latest/concepts/git_for_data/index.html

Built for production data work, without lock-in or migration

Bauplan is a data lakehouse designed to run real production workloads while staying simple, interoperable, and controllable.

Open lakehouse foundation

Bauplan is a data lakehouse built on open formats. Data is stored in object storage and managed using Apache Iceberg, giving you transactional guarantees, schema evolution, and time travel without tying you to a single engine or vendor.
You can run Python, SQL, and mixed workloads on the same tables. Curated data stays portable and accessible across your stack.

Platform

Bauplan uses a function-as-a-service execution model for data pipelines

Serverless compute, pure Python

Bauplan uses a function-as-a-service execution model for data pipelines. You write pure Python. Bauplan handles execution, isolation, and scaling. There are no clusters to manage, no long-running infrastructure, and no hidden runtime state. Each run is deterministic, isolated, and reproducible.

Enterprise-ready by design

Bauplan runs production-grade workloads without the operational overhead of traditional platforms.Deploy in single-tenant environments, use PrivateLink for network isolation, or bring your own cloud with BYOC. Your data stays in your object storage at all times. There is no copying or centralizing data into a proprietary system.

Bauplan is SOC 2 Type II compliant and includes built-in isolation, access controls, and auditability suitable for regulated environments.

Interoperable by design:
consume your data everywhere

Integrate

Run pipelines in Bauplan, then expose curated Iceberg tables to warehouses, lakehouses, and SQL engines. Connect tables directly to BI tools. Query data through Bauplan itself. Or use the Python SDK to work from your preferred notebook environment.You control how data is consumed and where computation happens.