Docs

Layout Presets

What it does: Switch between Vertical, Horizontal, Compact, Force, and Radial graph layouts.

How to use: Use the Layout dropdown in /playground after graph generation.

Tip: Use Horizontal for long pipelines and Radial for dependency exploration.

Focus + Search

What it does: Find nodes by name and isolate upstream/downstream dependencies. Matching nodes are highlighted with amber rings; non-matches dim to 20% opacity.

How to use: Use Search (or press /), then navigate with Enter/Shift+Enter. Toggle Focus mode (All Linked, Upstream, Downstream) to trace data flow.

Tip: Search for a target table first, then use Upstream to trace lineage inputs.

Dialect Parsing

What it does: Choose from 13 SQL dialects: PostgreSQL, MySQL, T-SQL, Snowflake, BigQuery, Redshift, Hive, Athena, Trino, MariaDB, SQLite, Oracle, and Teradata.

How to use: Select dialect from the SQL panel header in /playground, then click Visualize.

Tip: If parsing fails, verify dialect first before changing the query.

Export Graph

What it does: Export the current graph as PNG, SVG, Mermaid, or DOT (Graphviz) format.

How to use: Use the export buttons in the toolbar above the visualization.

Tip: Use PNG for sharing, SVG for slides, Mermaid for docs, and DOT for Graphviz or draw.io.

Optimization Hints

What it does: Automatic analysis of query patterns — detects SELECT *, missing indexes, Cartesian products, unused CTEs, and more.

How to use: Hints appear below the visualization after parsing. Click a hint to select the related node.

Tip: Focus on warnings first — they indicate potential performance issues.

Multi-Statement SQL

What it does: Paste multiple SQL statements separated by semicolons. Each statement gets its own tab.

How to use: Paste multi-statement SQL and click Visualize. Use the tabs above the diagram to switch between queries.

Tip: Tab labels are auto-generated from the first keyword and table name (e.g. "SELECT orders").

Fullscreen + Keyboard Shortcuts

What it does: Fullscreen mode for distraction-free viewing. Keyboard shortcuts for power users.

How to use: Press F for fullscreen, ? to see all shortcuts. Also: 1-5 for layouts, / for search, L for lineage.

Tip: Use Escape to exit fullscreen or clear selection and search.

Complexity Scoring

What it does: Complexity score (0–100) based on tables, joins, subqueries, CTEs, window functions, and conditions. Stats panel shows table usage histogram, join breakdown, and graph metrics.

How to use: Check the stat badges above the editor. Toggle the Stats panel for detailed breakdown.

Tip: Compare complexity scores before and after query refactors to measure improvement.

Accessibility

What it does: 3 colorblind-safe palettes (deuteranopia, protanopia, tritanopia) plus full keyboard navigation.

How to use: Use the Colors dropdown in the toolbar to switch palettes.

Tip: Palette preference is saved in your browser and persists across sessions.

Sample A: Customer Revenue Segments

Understand a CTE pipeline with joins, filters, aggregate, and CASE logic.

WITH order_totals AS (
  SELECT
    o.customer_id,
    SUM(o.amount) AS total_spent
  FROM orders o
  WHERE o.status = 'completed'
  GROUP BY o.customer_id
),
customer_summary AS (
  SELECT
    c.id AS customer_id,
    c.country,
    ot.total_spent,
    CASE
      WHEN ot.total_spent >= 5000 THEN 'enterprise'
      WHEN ot.total_spent >= 1000 THEN 'growth'
      ELSE 'starter'
    END AS segment
  FROM customers c
  JOIN order_totals ot ON c.id = ot.customer_id
)
SELECT country, segment, COUNT(*) AS customer_count, AVG(total_spent) AS avg_spent
FROM customer_summary
GROUP BY country, segment
ORDER BY avg_spent DESC;

Sample B: Weekly Product Trends

Review a query with date truncation, join, aggregate, and ranking window function.

WITH weekly_sales AS (
  SELECT
    DATE_TRUNC('week', o.created_at) AS sales_week,
    i.product_id,
    SUM(i.quantity * i.unit_price) AS revenue
  FROM orders o
  JOIN order_items i ON o.id = i.order_id
  WHERE o.created_at >= CURRENT_DATE - INTERVAL '90 days'
  GROUP BY DATE_TRUNC('week', o.created_at), i.product_id
),
ranked_products AS (
  SELECT
    ws.sales_week,
    p.category,
    p.name AS product_name,
    ws.revenue,
    DENSE_RANK() OVER (
      PARTITION BY ws.sales_week, p.category
      ORDER BY ws.revenue DESC
    ) AS revenue_rank
  FROM weekly_sales ws
  JOIN products p ON ws.product_id = p.id
)
SELECT sales_week, category, product_name, revenue
FROM ranked_products
WHERE revenue_rank <= 3
ORDER BY sales_week DESC, category, revenue DESC;