Kvery vs Avanty

Kvery is an SQL workspace that turns a written query into live tables, charts, REST endpoints, and shareable dashboards without you writing backend code. You connect MySQL, PostgreSQL, SQL Server, or MariaDB, write or generate SQL, and the platform builds the data views and APIs around that query in minutes instead of a multi-week sprint.

Most SQL clients stop at query results. Kvery ships the query as a product surface: auto-generated REST routes, drag-and-drop dashboards, scheduled runs with email or webhook delivery, and a built-in Model Context Protocol server so Claude, Cursor, or n8n can search and execute your saved queries with scoped tokens. That combination targets teams who want SQL-first delivery rather than a separate BI suite or hand-built API layer.

Developers, data analysts, and small product teams use Kvery to prototype internal tools, client reporting, and ops dashboards. Role-based workspaces, AES-256 encrypted connections, and native iOS and Android apps make it workable for production data when you need mobile access or tight permission boundaries.

Avanty sits inside Metabase as a Chrome extension and writes SQL from plain English prompts. It reads your connected schema, drafts queries in the editor, and explains existing SQL step by step so analysts spend less time fighting syntax.

Generic SQL copilots work in a blank editor. Avanty is scoped to Metabase: it knows your tables, respects custom schema names like datawarehouse.users, and opens from a command panel with Cmd Shift period on macOS or Ctrl Shift period on Windows. An inline diff viewer shows proposed edits before you accept them.

Data analysts and analytics engineers who live in Metabase get the most from Avanty. Business questions that used to mean a Slack ping and a half-written query can start as a natural language prompt, land in Metabase as a draft question, and move through review faster. A preview Slack integration even surfaces matching Metabase questions from channel messages.