Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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AdminForth
✓ verifiedFree
Open-source, agent-first admin-panel framework for Vue3/Node.js with auth, plugins and AI features to build back-office panels fast.
2.1K visits/mo
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Open Source Database Designs
✓ verifiedFreemium
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
27K visits/mo
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Wren AI Cloud
✓ verifiedFreemium
Open-source GenBI platform that turns plain-English questions into governed SQL, charts and dashboards for data teams.
43K visits/mo2.1K saves
Pricing
No public pricing
No public pricing
Free: $0/mo (20 monthly credits, 2 projects)
Essential: $179/mo (13,200 annual credits, unlimited projects)
Enterprise: $559/mo (24,000 annual credits, row/column controls)
Core features
- ✦CRUD admin panel from a database URL
- ✦Vue3 components and Tailwind theming with dark mode
- ✦Auth plugins: OAuth2/SSO, TOTP/WebAuthn 2FA
- ✦Audit log, S3 upload and CSV import/export plugins
- ✦AI plugins for autocomplete, translation and bulk data
- ✦Custom pages, dashboards and background jobs
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦Natural-language to SQL with instant charts
- ✦Semantic modeling layer (MDL)
- ✦Row-level and column-level data policies
- ✦20+ connectors (BigQuery, PostgreSQL, ClickHouse, Redshift)
- ✦Auto-generated GenBI dashboards
- ✦Embedded AI API with agent skills and memory
- ✦Cloud and self-hosted deployment
Use cases
- →Developers building internal back-office tools
- →Adding an admin panel to an existing database
- →Creating AI/agent-assisted back-office workflows
- →Self-hosting a customizable admin UI
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Self-serve analytics for non-technical teams
- →Building governed dashboards from a prompt
- →Embedding AI analytics into products
- →Cutting ad-hoc SQL requests to data teams
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