Open-source Snowflake and Fivetran alternative bundled together

A comprehensive guide to building a modern data warehouse with SQL Server, including ETL processes, data modeling, and analytics.

A curated list of open source tools used in analytics platforms and data engineering ecosystem

Qbeast-spark: DataSource enabling multi-dimensional indexing and efficient data sampling. Big Data, free from the unnecessary!

A data framework for biology. Makes your data queryable, traceable, reproducible, and FAIR. One API: lakehouse, lineage, feature store, ontologies, LIMS, ELN.

Sample Data Lakehouse deployed in Docker containers using Apache Iceberg, Minio, Trino and a Hive Metastore. Can be used for local testing.

Data Engine for Manual/Algo Trading: Download/Stream -> Clean -> Store. Supports Data Lakehouse Architecture. Clean Once and Forget.

SwiftLake: Java SQL engine built on Apache Iceberg and DuckDB for efficient lakehouse reads and writes

DatAasee - A Metadata-Lake for Libraries

This repository is a place for the Data Warehousing course at the Information Systems & Analytics department, Santa Clara University.

My M.Sc. dissertation: Modern Data Platform using DataOps, Kubernetes, and Cloud-Native ecosystem to build a resilient Big Data platform based on Data Lakehouse architecture which is the base for Machine Learning (MLOps) and Artificial Intelligence (AIOps).

The project aims to process Formula 1 racing data, create an automated data pipeline, and make the data available for presentation and analysis purposes.

This repo provides a step-by-step approach to building a modern data warehouse using PostgreSQL. It covers the ETL (Extract, Transform, Load) process, data modeling, exploratory data analysis (EDA), and advanced data analysis techniques.

Complete open-source data platform with Airbyte, Dremio, dbt, and Apache Superset - Documented in 18 languages

🌊 Git-like Version Control for Data with Nessie, Iceberg, and Spark

This project implements an end-to-end techstack for a data platform, for local development.

🚀 Scalable near-real-time data pipeline using Apache Iceberg, Spark, Kafka, and Trino. ACID-compliant JSON ingestion, processing, and analytics. Dockerized for easy deployment. #DataEngineering #DataLake

Building a modern data warehouse with SQL Server, including ETL processes, data modeling and analytics.

Data lakehouse at home with docker compose

This project implements a complete Modern Data Warehouse using SQL-based ETL pipelines and Medallion Architecture (Bronze/Silver/Gold). It includes raw data ingestion, transformation layers, dimensional modeling, data marts, and analytical reporting structures suitable for business intelligence and data engineering workflows.