Demos for Nessie. Nessie provides Git-like capabilities for your Data Lake.

Query a Virtual Knowledge Graph over Iceberg in Trino, Nessie as Catalog, and use minio to replace AWS S3

Apache Flink and Apache Iceberg Demo

Spring boot Spark Iceberg Demo

Transfer data from relational database tables, views, and query results to Apache Iceberg tables

Apache Iceberg Lakehouse using MinIO, Trino and Nessie.

A fully containerized multi-service environment to prototype end-to-end ETL workflows.

An AI-powered Lakehouse platform with Sales Copilot features, enabling smart retail analytics from ingestion to insight.

A sample setup modern data lakehouse with MinIO as S3 Like, Nessie for data catalog and version control system to data lake, Dremio as Query Engine for SQL Like to catalog lakehouse, Apache NiFi as data streaming to handle ETL process, Metabase as visualization dashboard to get insight for forecasting or business decision in the future.

The AI-powered backend for the BarterBrAIn Flutter app. Built with Firebase Cloud Functions and Google Gemini 2.5 Flash to handle intelligent product valuation, real-time negotiation coaching, and sustainability impact calculations.

Real‑time streaming lakehouse stack: Kafka produces JSON events that Kafka Connect (Iceberg Sink) writes transactionally into Apache Iceberg tables versioned by Nessie, stored in MinIO (S3 compatible), and queried with Trino. Includes automatic schema evolution (additive), table bootstrap, and a Python data simulator.

We will create a sample lakehouse using Docker, execute an ETL process with Spark, and then access the data in the Iceberg table format from the Nessie Catalog.

Case Santander

This pipeline is a mini-project to get comfy with MinIO, Iceburg, Dremio and Nessie, Spark and superset.

Data Lakehouse implementations showcasing two approaches: one built with Open Source technologies and another with Databricks