Apache Doris is an easy-to-use, high performance and unified analytics database.

The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.

Free universal database tool and SQL client

Pytest Fixtures that let you actually test against external resource (Postgres, Mongo, Redshift...) dependent code.

Open Source Feature Flagging and A/B Testing Platform

GUI application for calculating human-visible colors of celestial bodies from their photometric data

Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.

Fluent migrations framework for .NET

Privacy and Security focused Segment-alternative, in Golang and React

pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days

Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.

LePHARE is a code for calculating photometric redshifts.

Python SQL Parser and Transpiler

Database Subsetting and Relational Data Browsing Tool.

CDK Construct for creating a bastion host to forward a connection to several AWS data services inside a private subnet from your local machine

Sample code to set up a data sharing between two Redshift clusters

A visual data pipeline builder with various backends

Apply Data Engineering to Personal Finance

A Python script extracts data from Zillow and stores it in an initial S3 bucket. Then, Lambda functions handle the flow: copying the data to a processing bucket and transforming it from JSON to CSV format. The final CSV data resides in another S3 bucket, ready to be loaded into Amazon Redshift for in-depth analysis. QuickSight for visualizations