Basedash vs SQL Mocker

Basedash is an AI-native business intelligence platform for asking plain-English questions about live company data and turning answers into governed dashboards and automated reports. Its AI analyst validates generated SQL against connected schemas and displays the SQL behind each answer. Users describe the metrics they want to follow, and Basedash assembles charts, KPIs, and dashboard layouts. Teams can define dimensions, measures, and segments for reuse across chat, dashboards, and automations. A managed DuckDB warehouse centralizes data synced from more than 750 sources. Listed connections include PostgreSQL, MySQL, Snowflake, BigQuery, Redshift, Databricks, Salesforce, HubSpot, and Stripe. The agent answers questions in Slack with chart images; reports and alerts can go to Slack and email. Deployment options are managed cloud, private VPC, or self-hosting with Docker, Kubernetes, and Helm. Security listings include SOC 2 Type II, encryption, SSO, SCIM, role-based and row-level security, and audit logs.

SQL Mocker is a web app that generates SQL from natural-language questions using a reviewed copy of database schema metadata. Users can provide schema details through a file, pasted metadata, manual setup, or results from an extraction script run in their own database. Its workspace can detect, review, edit, or add table relationships, including ones missing from the supplied metadata. Existing SQL can also be submitted for explanation, review, improvement, formatting, conversion, troubleshooting, or mapping columns and joins. SQL Mocker can generate dummy data from a schema to preview results and test query logic without production rows. Its homepage lists 17 supported database systems, including SQL Server, PostgreSQL, MySQL, Oracle, Snowflake, BigQuery, and MongoDB. It says it needs no database credentials for schema-based generation and does not connect to a live customer database. Generated SQL is presented for review and copying; users run it themselves in their own database tool. Saved projects sync to the user account and are cached in the browser, with backup files available from History. The free Explore plan includes 50 AI queries total and five saved projects; paid plans are marked as coming soon.