Offline & Private
Analyze SQL locally. Your SQL never leaves your machine.
Column-level lineage and impact analysis across dialects. No data leaves your machine.
Track data flow across tables and transformations
See what breaks before you ship changes
Visualize entity relationships from SQL
Analyze SQL locally. Your SQL never leaves your machine.
Trace fields across complex SQL with CTEs and window functions.
See what breaks when a table/column changes before shipping.
Support for 30+ SQL dialects including CTE, window functions, and cross-dialect parsing
The Challenge: Your team needs to understand a 40-line SQL query calculating 90-day customer lifetime value with currency conversions. How long would it take to trace every column, join, and transformation manually?
WITH completed_orders AS (
SELECT o.order_id, o.customer_id,
o.order_date, o.amount, o.currency
FROM raw.orders o
WHERE o.status = 'COMPLETED'
),
fx AS (
SELECT f.currency_code, f.rate_to_usd, f.valid_on
FROM dim.exchange_rates f
),
orders_usd AS (
SELECT
o.customer_id,
o.order_date,
o.amount * COALESCE(f.rate_to_usd, 1) AS amount_usd
FROM completed_orders o
LEFT JOIN fx f
ON f.currency_code = o.currency
AND f.valid_on = DATE_TRUNC('day', o.order_date)
),
recent AS (
SELECT customer_id, order_date, amount_usd
FROM orders_usd
WHERE order_date >= CURRENT_DATE - INTERVAL '90' DAY
)
SELECT
customer_id,
SUM(amount_usd) AS ltv_90d
FROM recent
GROUP BY customer_id;
raw.orders
and dim.exchange_rates
feeding your KPI
amount × rate_to_usd
creates normalized values
SUM(amount_usd)
rolls up to ltv_90d
per customer
Gudu SQL Omni | Online platforms | |
---|---|---|
Privacy | Offline, local parsing | Uploads or agents |
Setup | Install & go | Accounts & connectors |
Speed | Instant | Network latency |
Granularity | Column-level | Varies |
"Finally, SQL lineage that works offline. No more worrying about sensitive data leaving our machines."
— Senior Data Engineer, Fortune 500"The column-level lineage is incredibly accurate. Saved us hours debugging data pipelines."
— Analytics Lead, Tech Startup"Impact analysis before deploying changes is a game-changer. We catch issues before production."
— Data Architect, Healthcare$10/month
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No. Parsing and analysis happen locally. No SQL leaves your machine.
Works across major dialects (e.g., Snowflake, BigQuery, Redshift, Databricks, Postgres).
Subscribe for $10/month (Launch Week special). Cancel anytime. Your subscription remains valid until the next billing cycle.
After subscribing, copy your license key to the extension's Activate/Upgrade command.
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Optimized to handle SQL files up to 10MB instantly. Column-level analysis stays fast.
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