Amazon SageMaker Lakehouse vs Bauplan

Amazon SageMaker Lakehouse has no write-up on Specifiction yet; its figures are above.

Bauplan is a data lakehouse for running Python and SQL pipelines directly on Apache Iceberg tables in a user's object storage, without managing servers or clusters. It uses serverless execution for Python pipelines and supports Python, SQL, and mixed workloads on the same tables. Data branches, isolated runs, atomic publishes, and rollback are intended to safeguard changes to production data. Bauplan also describes workflows where AI agents build pipelines, explore data, and manage a lakehouse through its MCP Server and Skills. Integrations listed include Airflow, Prefect, Dagster, Temporal, DBOS, Jupyter, Marimo, Streamlit, Snowflake, BigQuery, Metabase, Superset, Fivetran, and Airbyte. Bauplan says customer data stays in the customer's S3 bucket and offers PrivateLink or bring-your-own-cloud options. Its free Sandbox uses a shared environment where all data is public, which the company recommends for toy projects and demos rather than company data. Dedicated costs $700 a month after the first 14 days free and includes a dedicated private instance, data in the customer's S3, 10GB memory, and unlimited queries, users, and agents. Enterprise pricing is custom. Bauplan states that it is SOC 2 Type II compliant.