Baserow is a no-code platform that lets teams build custom databases, internal apps, dashboards, and AI-powered workflows without writing code. Designed as an open-source alternative to Airtable, it combines the familiarity of spreadsheets with advanced data organization, automation, and visualization tools — all while ensuring full data ownership through self-hosted or cloud deployments. Trusted by over 150,000 users, it’s built for teams needing compliance, scalability, and vendor neutrality.
Built with Django, Vue.js, and PostgreSQL, Baserow offers a headless, API-first architecture with RESTful endpoints and OpenAPI schema support. It supports deployment via Docker, Helm, Heroku, AWS, DigitalOcean, Cloudron, Railway, and Render, enabling full control over infrastructure. Its AI assistant Kuma enables natural language database creation, and all non-enterprise features are MIT-licensed for commercial use.
What You Get
- Spreadsheet-Database Hybrid - A unified interface combining spreadsheet simplicity with relational database structure, supporting grid, gallery, kanban, calendar, timeline, form, and survey views.
- AI Assistant (Kuma) - Create databases, fields, and applications using natural language prompts, enabling non-technical users to generate structured data systems without manual configuration.
- No-Code Application Builder - Build and publish custom web applications (e.g., CRM, risk management, ESG tracking) with drag-and-drop pages, forms, and dashboards — deployable on your own domain.
- Visual Automations - Create workflows with triggers, conditions, branches, and loops using native actions like HTTP requests, email, and webhooks, plus third-party integrations to eliminate manual processes.
- Custom Dashboards - Visualize data with charts and metrics, designed for management reporting and real-time KPI tracking across departments like marketing, manufacturing, and risk management.
- GDPR, HIPAA, and SOC 2 Type II Compliance - Enterprise-grade data security and privacy controls with audit-ready logs, encryption, and compliance certifications for regulated industries.
- Self-Hosted & Multi-Deployment Support - Deploy on Docker, Helm, AWS, DigitalOcean, Cloudron, Railway, or Heroku with no data restrictions — full control over infrastructure and data residency.
- Headless API & OpenAPI Schema - Full RESTful API access with documented endpoints and schema.json for integration with external tools, custom frontends, or third-party automation platforms.
Common Use Cases
- Running a risk management system - A compliance officer uses Baserow to track incidents, policies, and audits with custom forms, automations for alerting, and dashboards for executive reporting — all while meeting SOC 2 requirements.
- Building an internal CRM for real estate agents - A product team creates a no-code CRM with client profiles, deal pipelines, and automated follow-up emails using Baserow’s application builder and HTTP webhooks.
- Managing ESG data across global teams - A sustainability team ingests CSV data from multiple sources, structures it in Baserow, and builds a dashboard to track carbon metrics and compliance status with AI-assisted field generation.
- Replacing Excel spreadsheets for project tracking - A project manager converts static spreadsheets into a live, collaborative database with kanban views, automations for deadline reminders, and embedded forms for team updates.
Under The Hood
Architecture
- Monolithic backend with tightly coupled Django apps sharing models and services, lacking formal interface boundaries and dependency injection
- Service layer implemented via custom managers and classes but with hard-coded dependencies and no centralized orchestration
- Frontend and backend are fully decoupled via REST and WebSockets, though frontend state management remains basic
- Plugin system supports external module injection but lacks runtime lifecycle control or sandboxing
- Asynchronous tasks managed through Celery and Redis, but task definitions are fragmented without unified monitoring
- Configuration is environment-variable driven, leading to brittle deployments and inconsistent environment handling
Tech Stack
- Python 3.9+ backend powered by Django REST Framework with extensible plugin architecture
- PostgreSQL with pgvector extension for relational and vector data capabilities
- Redis serving as cache, task broker, and real-time communication layer
- Nuxt.js 3 frontend with TypeScript, built via Docker for SSR and static generation
- Caddy as production reverse proxy handling HTTPS, WebSocket upgrades, and static asset serving
- Multi-stage Docker builds supporting diverse deployment targets including Heroku, Render, and standalone setups
Code Quality
- Comprehensive test coverage spanning unit, integration, and end-to-end scenarios with robust fixtures and performance validation
- Strong type safety and consistent, domain-driven naming across both Python and TypeScript codebases
- Sophisticated error handling with custom exceptions and structured validation in security-critical paths
- Strict linting and code quality enforcement with minimal noqa annotations, indicating disciplined code hygiene
- Clear modular separation between core, enterprise, and frontend layers, enabling sustainable extension
- Automated CI/CD pipelines with query analysis and UI automation ensuring reliability across complex workflows
What Makes It Unique
- Real-time collaboration powered by operational transforms embedded directly in the database layer, eliminating external real-time services
- Extensible field-type system allowing domain-specific data modeling via pluggable modules
- Dynamic API generation that automatically adapts REST and WebSocket endpoints to schema changes
- Built-in data sync connectors with native OAuth2 and webhook support, not added as afterthoughts
- Granular client-side undo/redo stack implemented at the UI state level, not as a simple history buffer
- Automatic schema migration system that safely applies structural changes during active user editing