Apache Superset is a Data Visualization and Data Exploration Platform
Repository for Docker Image of Apache-Superset. [Docker Image: https://hub.docker.com/r/abhioncbr/docker-superset]
📡 Real-time data pipeline with Kafka, Flink, Iceberg, Trino, MinIO, and Superset. Ideal for learning data systems.
👗 📄 A catalog of CSS templates I developed to style the dashboard in Apache Superset
A local-first lakehouse reference architecture for production-minded data platform engineering.
MCP server for managing Apache Superset — 128+ tools for dashboards, charts, datasets, SQL Lab, access control
This is my Apache Airflow Local development setup on Windows 10 WSL2/Mac using docker-compose. It will also include some sample DAGs and workflows.
Demostrate apache superset integrated with django application, with custom authentication layer
An End-to-End ETL data pipeline that leverages pyspark parallel processing to process about 25 million rows of data coming from a SaaS application using Apache Airflow as an orchestration tool and various data warehouse technologies and finally using Apache Superset to connect to DWH for generating BI dashboards for weekly reports
A walkthrough to deploy Apache Superset on Google Cloud Run
A batch processing data pipeline, using AWS resources (S3, EMR, Redshift, EC2, IAM), provisioned via Terraform, and orchestrated from locally hosted Airflow containers. The end product is a Superset dashboard and a Postgres database, hosted on an EC2 instance at this address (powered down):
PyDynamoDB is a Python DB-API 2.0 (PEP 249) client for Amazon DynamoDB, with a SQLAlchemy dialect included. It is used as a database driver in Apache Superset.
A Smart Traffic Management System for Ho Chi Minh City, Vietnam leveraging batch and real-time data processing, intuitive dashboards, and monitoring tools to optimize traffic flow, enhance safety, and support sustainable urban mobility through advanced analytics and user-friendly applications.
End-to-end data platform for Cartola FC: Airflow pipelines ingest match and player data into a Hadoop/Hive data lake, with DataHub lineage and Superset dashboards. Docker Compose quickstart included
Apache Superset Kubernetes Operator
Lambda data architecture reference project — dbt medallion models, Airflow DAGs, Superset dashboards, and Marquez lineage for Iowa retail and Covid-19 analytics on GCP
Production-ready Apache Superset with DuckLake integration. Stateless analytics architecture using DuckDB for compute, PostgreSQL for metadata, and S3/GCS/MinIO for data lake storage. Includes Docker Compose, Kubernetes Helm charts, BigQuery Integration, and CI/CD workflows. Supports MotherDuck cloud integration.