Build your medallion architecture in pure Python. No vendor lock-in, no infrastructure management.
Raw, immutable data: your source of truth for audits and reprocessing.
Cleaned, flattened, validated, and standardized data, used to build downstream pipelines.
Business-ready metrics, aggregates, and ML features optimized for consumption.
Quality: Data quality issues are caught early, before they cascade.
Performance: Heavy transformations are done once, punctual aggregations are done.
Governance: Complete audit trail with documented transformation rules.
Team velocity: Engineers own Bronze/Silver, analysts and business users work directly with Gold.
Build the entire medallion flow in pure Python and SQL using Pandas, Polars and DuckDB. No Spark, no JVM, no cluster overhead. Bauplan handles execution with Arrow under the hood, so you focus purely on transformations and logic.
Define data quality tests as code right next to your pipeline steps. Checks like null detection and uniqueness run directly on in-memory tables, failing fast if issues appear. No extra pipelines, no waiting to validate data, no extra compute wasted.
Bauplan unifies your Iceberg lakehouse, data branching, and execution in one simple system. Spin up branches for medallion layers, run DAGs in isolation, and merge back seamlessly: no catalog wrangling, no custom glue code.
Bronze, Silver, and Gold datasets live in distinct namespaces, making lineage and promotion clear. Combined with branch-test-merge, this ensures production remains stable and reproducible as data progresses through each stage.
Raw data lands in the Bronze layer. Bauplan handles ingestion into Iceberg tables on isolated branches, so you can safely load from S3 without touching production.
Silver tables are created with Python models and SQL. Transformations live alongside expectations, so data quality checks run as part of the pipeline. Fail fast, fix early.
Validated data moves into the Gold layer. Aggregations, joins, and business-ready tables are promoted only after tests succeed, keeping production consistent and reliable.
Raw event ingestion from 50+ sources
Standardized events with business validation
Real-time metrics and aggregations