wrapper for multiple linkml storage engines
Post4 is an indirect threaded Forth interpreter written in C.
Set up an encrypted iOS Database with only 1 line of code!
CoreDataServices is a suite of helper classes and extensions to help to remove some of the boilerplate that surrounds using Core Data.
A starting point for a data stack using Python, Apache Airflow and Metabase.
🧱 Tinkering around with a bunch of open source data tools.
A minimal modern data stack with working data pipelines in a single Docker container.
Set up an encrypted iOS Database with only 1 line of code!
Demo data stack using Dagster + Airbyte + dbt
Modular data platform building blocks wired through explicit contracts, not hidden dependencies
Introduction to using and scaling dagster
🦆🔨 Glue Duckle + DuckQuery + Shaper into one DuckDB-native data stack: ETL → Query → Visualize, zero format conversion.
This repo provides a POC to demostrate how a portable data stack can provide an end-to-end ETL process with simple BI. It's calling PiwikPRO API for a demo account and using GCP service account to interact with Google Sheets.
Simple, lightweight Core Data library that eases migrations and reduces boilerplate
Simple stack imlementation on ES6
Creating a modern data stack in Kubernetes with open-source products, both on-premises and cloud-agnostic, is an increasingly popular approach. By leveraging Kubernetes for container orchestration, you can deploy and manage data processing, storage, and analysis tools more efficiently.
Lakehouse starter kit for small teams (1-5). Extract data with dlt, transform with dbt, visualize with Superset. S3-compatible storage with MinIO. Easy to scale.
Mode is a collaborative business intelligence and analytics platform that unites data and business teams around a single analytical workflow. Built by analysts for analysts, Mode combines ad hoc SQL exploration, Python and R notebooks, interactive dashboards, self-serve reporting, and custom data applications on top of connected data warehouses.
Riverpool (riverpool.ai) is an early-stage, pre-launch startup building what it describes as the "post-modern analytics data stack" — a continuously circulating, self-refreshing approach to analytics data rather than a stagnant warehouse.
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