{"id":30687644,"url":"https://github.com/kot-behemoth/kitsuna-data","last_synced_at":"2025-09-02T00:04:44.916Z","repository":{"id":292246914,"uuid":"980247422","full_name":"kot-behemoth/kitsuna-data","owner":"kot-behemoth","description":"Self-hosted one-person data 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/\u003e\n\u003cdiv align=\"center\"\u003e\n  \u003c!-- \u003ca href=\"https://github.com/othneildrew/Best-README-Template\"\u003e --\u003e\n  \u003c!--   \u003cimg src=\"images/logo.png\" alt=\"Logo\" width=\"80\" height=\"80\"\u003e --\u003e\n  \u003c!-- \u003c/a\u003e --\u003e\n\n  \u003ch3 align=\"center\"\u003eKitsuna Data\u003c/h3\u003e\n\n  \u003cp align=\"center\"\u003e\n    Self-hosted one-person data platform\n    \u003cbr /\u003e\n    \u003cbr /\u003e\n  \u003c/p\u003e\n\u003c/div\u003e\n\n\u003c!-- TABLE OF CONTENTS --\u003e\n\u003cdetails\u003e\n  \u003csummary\u003eTable of Contents\u003c/summary\u003e\n  \u003col\u003e\n    \u003cli\u003e\n      \u003ca href=\"#about-the-project\"\u003eAbout The Project\u003c/a\u003e\n      \u003cul\u003e\n        \u003cli\u003e\u003ca href=\"#main-features\"\u003eMain Features\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#goals\"\u003eGoals\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#tech-stack\"\u003eTech Stack\u003c/a\u003e\u003c/li\u003e\n      \u003c/ul\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\n      \u003ca href=\"#getting-started\"\u003eGetting Started\u003c/a\u003e\n      \u003cul\u003e\n        \u003cli\u003e\u003ca href=\"#prerequisites\"\u003ePrerequisites\u003c/a\u003e\u003c/li\u003e\n        \u003cli\u003e\u003ca href=\"#installation\"\u003eInstallation\u003c/a\u003e\u003c/li\u003e\n      \u003c/ul\u003e\n    \u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#usage\"\u003eUsage\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#roadmap\"\u003eRoadmap\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#contact\"\u003eContact\u003c/a\u003e\u003c/li\u003e\n    \u003cli\u003e\u003ca href=\"#inspiration\"\u003eInspiration\u003c/a\u003e\u003c/li\u003e\n  \u003c/ol\u003e\n\u003c/details\u003e\n\n## About The Project\n\nThis is a concept for what a Rails-inspired small data platform for startups and SMEs could look like. After using a variety of end-to-end solutions like DOMO, Keboola, Mozart Data and others, I keep wishing there was something that would do the 80% of ELT + BI out-of-the-box, without the price surprises.\n\nThis project is an attempt to stitch together a set of solid and reliable open-source tools that combine into a lean platform where one data engineer can own the entire lifecycle. From ELT, to data modelling, to deploying and scaling in production.\n\n![Kitsuna overview diagram](docs/docs/assets/Overview.png)\n\n### Main Features\n\n1. **🧪 From laptop to production in minutes** - Develop locally with DuckDB, deploy with the same code. No more \"it works on my machine\" problems.\n\n1. **⚡ Lightning-fast analytics on any data size** - DuckDB's column-oriented design handles gigabytes of data on modest hardware. Query billions of rows in seconds.\n\n1. **📊 Beautiful dashboards** - Drag-and-drop dataviz with Metabase. Perfect for everyone - tech and non-tech alike.\n\n1. **💸 Scale without breaking the bank** - Enterprise-grade data stack for as little as $30/month. DuckDB + SQLMesh's efficiency means less compute costs than Snowflake or BigQuery.\n\n1. **🔄 30+ ready-to-use integrations** - Instant integrations with dlt for Stripe, GitHub, Salesforce, and more. Connect your SaaS tools with minimal code.\n\n1. **🤖 Just ask your DB** - Ask questions in plain English with DuckDB's MCP. Get immediate answers without writing complex queries.\n\n1. **🔍 End-to-end data lineage** - SQLMesh tracks transformations from raw to gold data. Understand exactly where metrics come from and debug easily.\n\n\u003e [!CAUTION]\n\u003e The project is very much in the pre-alpha stage. This is more of an experiment and is not meant for produciton workloads.\n\n### Goals\n\n- Local-first development for the entire stack.\n- Support companies that can't afford heavy, expensive data tools or large teams.\n- No \"SSO tax\" - all tools should be either fully free, or affordable once deployed in serious prod use case.\n- No k8s, so a small data team can be self-sufficient .\n- Cheap path to production and scaling.\n\n### Tech Stack\n\n- _Extract_ (planned): [dlt](https://dlthub.com/)\n- Transform: [SQLMesh](https://sqlmesh.readthedocs.io/en/stable/)\n- Data Storage: [DuckDB](https://duckdb.org/)\n- BI / data viz: [Metabase](https://www.metabase.com/)\n- Deployment: [Dokploy](https://dokploy.com/)\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n## Getting Started\n\n### Prerequisites\n\nThis is an example of how to list things you need to use the software and how to install them.\n\n* `uv`\n* `mise` (recommended)\n* `claude` (recommended)\n\n### Installation\n\n1. Clone this repository\n2. Download the DuckDB driver for Metabase:\n   ```bash\n   make download-duckdb-driver\n   ```\n3. Start the services:\n   ```bash\n   docker-compose up -d\n   ```\n4. Access Metabase at http://localhost:3000\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n## Usage\n\nTODO\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n## Deployment\n\nThis project can be deployed to DigitalOcean/Hetzner/EC2 using Dokploy with the following architecture:\n\n1. **Metabase Container**:\n   - Dedicated hostname (e.g., metabase.yourdomain.com)\n   - Access to mounted DuckDB volume\n\n2. **dlt + SQLMesh Container**:\n   - Combined container for data processing\n   - Access to the same DuckDB volume\n\n3. **Shared Storage**:\n   - Used for persistent DuckDB storage\n\n## Roadmap\n\n- [x] Add SQLMesh\n- [x] Add MCP for DuckDB\n- [ ] Add dlt\n    - [ ] Implement as an example: [Exploring StarCraft 2 data with Airflow, DuckDB and Streamlit \\| by Volker Janz \\| Data Engineer Things](https://blog.det.life/exploring-starcraft-2-data-with-airflow-duckdb-and-streamlit-7c0ad79f9ca6)\n- [x] Add Dokku deployment configuration\n    - [ ] Create a DigitalOcean box for a public demo\n- [ ] Add installation docs\n- [ ] Add usage docs\n- [ ] Add Aider docs\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n## Contact\n\nGreg Goltsov - [@gregoltsov](https://x.com/gregoltsov), [gregoltsov.bsky.social](https://bsky.app/profile/gregoltsov.bsky.social).\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n\n## Inspiration\n\nHere are some projects which inspired my thinking and this project:\n\n* [Modern Data Stack in a Box with DuckDB](https://duckdb.org/2022/10/12/modern-data-stack-in-a-box.html)\n* [MDS-in-a-box: Monte Carlo simulation of the NBA season](https://github.com/matsonj/nba-monte-carlo)\n* [Exploring StarCraft 2 data with Airflow, DuckDB and Streamlit](https://blog.det.life/exploring-starcraft-2-data-with-airflow-duckdb-and-streamlit-7c0ad79f9ca6)\n\n\u003cp align=\"right\"\u003e(\u003ca href=\"#readme-top\"\u003eback to top\u003c/a\u003e)\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkot-behemoth%2Fkitsuna-data","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkot-behemoth%2Fkitsuna-data","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkot-behemoth%2Fkitsuna-data/lists"}