Learn AI for Database

Get up and running with AI for Database in under five minutes. Connect your first database, ask a question, and see results.

Learn how to write effective natural-language questions and understand how AI for Database translates them into SQL.

A general overview of how database connections work, including security, permissions, and supported databases.

Step-by-step guide to connecting PostgreSQL, including user creation, permissions, SSL configuration, and SSH tunnels.

Connect MySQL or MariaDB to AI for Database with read-only access, SSL, and SSH tunnel support.

Connect MongoDB and MongoDB Atlas. Learn how AI for Database translates natural language into aggregation pipelines.

Connect Microsoft SQL Server, Azure SQL, or Amazon RDS SQL Server with Windows or SQL authentication.

Use Google Sheets as a data source. AI for Database reads your spreadsheets and lets you query them with natural language.

Diagnose and fix common connection issues including timeouts, SSL errors, permission denied, and firewall blocks.

Deep dive into how AI for Database converts plain English into SQL, including tips, examples, and advanced techniques.

Access, search, and manage your past queries. Re-run, favorite, or share any previous question.

Understand result formats including tables, charts, and single values. Export data as CSV, JSON, or to dashboards.

Power-user techniques: parameterized queries, variables, cross-database joins, and scheduled queries.

Build your first live dashboard by combining multiple queries into a visual overview. Customize layout and refresh schedules.

All widget types: metric cards, tables, bar charts, line charts, pie charts, and text blocks. Configuration and styling options.

Share dashboards via links, embeds, email digests, or Slack. Manage viewer permissions and access controls.

Build automated workflows that run queries, check conditions, and take actions based on your database data.

All trigger types: scheduled (cron), webhook, database change, and manual triggers. Configuration and examples.

Available workflow actions: email, Slack, webhooks, and more. Templating with query results and configuration.

Pre-built workflow templates for common automation patterns: alerts, reports, data syncs, and notifications.

Create data-driven alerts that notify you when database conditions are met. Step-by-step setup guide.

Configure notification channels: email, Slack, webhooks, PagerDuty, and more. Test and manage channel settings.

All condition types: thresholds, change detection, anomaly detection, and compound conditions. Examples for each.

How AI for Database protects your data: encryption, read-only access, network security, and compliance certifications.

Role-based access control: admin, editor, and viewer roles. Custom roles and fine-grained permissions on Enterprise.

Track who did what and when. Search audit logs, export for compliance, and set up log forwarding.

Run AI for Database in your own infrastructure. Docker, Kubernetes, and bare-metal deployment guides.

Introduction to the AI for Database REST API. Base URLs, versioning, rate limits, and response formats.

API key management, OAuth flows, token scopes, and security best practices for API authentication.

Complete API reference: queries, dashboards, workflows, connections, and team management endpoints.