Stop guessing why a query is slow — get a clear diagnosis, a faster rewrite and the indexes that actually move the needle.
Paste a slow query and your dialect — get a plain-language diagnosis of what is slow, a faster rewrite that returns identical results and the exact indexes worth adding.
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3–8× faster · 2 full-table scans eliminated
Rewrote comma join to explicit JOIN, removed function wrap on email column
Function wrapping prevents the index on email from being used — rewrite as email = lower($1).
SELECT
o.id, o.amount, o.status,
c.email, c.name
FROM orders o
JOIN customers c ON o.customer_id = c.id
WHERE c.email = lower($1)
AND o.status <> 'cancelled'
ORDER BY o.created_at DESCCREATE INDEX ON customers (lower(email));
CREATE INDEX ON orders (customer_id, status, created_at DESC);Validate the rewrite returns identical rows before replacing anything in production.
Every card is something members actually do inside Datamata — not a vague promise.
Full scans, non-sargable filters and accidental cartesian joins — named in plain language and ranked by impact.
Same results, fewer bottlenecks — sargable predicates, tightened joins and projection instead of SELECT star.
CREATE INDEX statements built from your real filters and join keys — not generic advice you have read ten times.
Plain-language diagnosis of every performance issue, ranked by impact
Feature deep-dives
See it work
Full scans, non-sargable filters and accidental cartesian joins — named in plain language and ranked by impact.
Try SQL Optimizer3–8× faster · 2 full-table scans eliminated
Rewrote comma join to explicit JOIN, removed function wrap on email column
Function wrapping prevents the index on email from being used — rewrite as email = lower($1).
SELECT
o.id, o.amount, o.status,
c.email, c.name
FROM orders o
JOIN customers c ON o.customer_id = c.id
WHERE c.email = lower($1)
AND o.status <> 'cancelled'
ORDER BY o.created_at DESCCREATE INDEX ON customers (lower(email));
CREATE INDEX ON orders (customer_id, status, created_at DESC);Validate the rewrite returns identical rows before replacing anything in production.
Go deeper
Same results, fewer bottlenecks — sargable predicates, tightened joins and projection instead of SELECT star.
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CREATE INDEX statements built from your real filters and join keys — not generic advice you have read ten times.
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Real decisions, not generic templates. Every workflow runs on live market data so your moves are backed by what employers are asking for now.
Plain-language diagnosis of every performance issue, ranked by impact
A rewritten query that keeps identical results but drops the obvious bottlenecks
Concrete CREATE INDEX statements tuned to your filters, joins and sort order
Quick start guide
Paste a slow query, pick its dialect and get a ranked diagnosis, a faster rewrite and copy-pasteable index statements in seconds.
Drop in the full SELECT and choose the warehouse it runs on so casts and index syntax match.
Tip: The whole query beats a fragment — joins and subqueries are where most slow plans hide.
Optional but powerful — paste EXPLAIN output and a note on table sizes to ground the diagnosis in your real plan.
Tip: EXPLAIN ANALYZE is best where your warehouse supports it because it shows actual rows not estimates.
Read the ranked diagnosis, copy the rewritten query and add the suggested indexes one at a time.
Tip: Validate the rewrite returns identical rows before you replace anything in production.
Pro members get unlimited optimizations across every dialect — handy during an incident or a query-tuning sprint.
What's included
Plain-language diagnosis of every performance issue, ranked by impact
A rewritten query that keeps identical results but drops the obvious bottlenecks
Concrete CREATE INDEX statements tuned to your filters, joins and sort order
Dialect-aware for Postgres, MySQL, BigQuery, Snowflake and DuckDB
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$9.99/moUnlimited optimizations, all dialects and EXPLAIN-aware tuning
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