The Lakehouse Engine is a configuration driven Spark framework, written in Python, serving as a scalable and distributed engine for several lakehouse algorithms, data flows and utilities for Data Products.

A modern data marketplace that makes collaboration among diverse users (like business, analysts and engineers) easier, increasing efficiency and agility in data projects on AWS.

Apache Doris MCP Server

Unified storage framework for the entire machine learning lifecycle

Modern serverless lakehouse implementing HOOK methodology, Unified Star Schema (USS), and Analytical Data Storage System (ADSS) principles on Adventure Works. Features programmatic model generation, event-enhanced Puppini bridges, and temporal resolution across DAS/DAB/DAR layers.

🦆 Batch data pipeline with Airflow, DuckDB, Delta Lake, Trino, MinIO, and Metabase. Full observability and data quality.

📡 Real-time data pipeline with Kafka, Flink, Iceberg, Trino, MinIO, and Superset. Ideal for learning data systems.

Creation of a data lakehouse and an ELT pipeline to enable the efficient analysis and use of data

Lakevision is a tool which provides insights into your Apache Iceberg based Data Lakehouse.

Feature demos, integration guides & hands-on labs/projects using Kpow, Flex, Kafka, Flink, Iceberg & more

Building Data Lakehouse by open source technology. Support end to end data pipeline, from source data on AWS S3 to Lakehouse, visualize and recommend app.

The Metadata Driven framework for Databricks Lakeflow Declarative Pipelines (formerly Delta Live Tables). Metadata framework that generates production ready Pyspark code for Lakeflow Declarative Pipelines

A multi-modal Python library for benchmarking lakehouse engines and ELT scenarios, supporting both industry-standard and novel benchmarks.

Databricks DLT Apparel Pipeline Project: Learn medallion architecture, streaming, and data engineering with Delta Live Tables. Includes synthetic data, step-by-step guide, and certification prep.

Open source stack lakehouse

Unlocking the Power of Health Data With a Modern Data Lakehouse

From FHIR ingestion to patient outcomes analysis

This project implements a Lakehouse Medallion Architecture using modern Data Stack tools such as Fivetran, Snowflake and dbt. The ficticious organization is an e-commerce company.

Write-Audit-Publish on the lakehouse in pure Python with bauplan and DBOS

Data Lakehouse moderno com MinIO, DuckDB, dbt, metabase e airflow