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Pre-deploy safety

Bulk data operations that do not take down production.

One-off migrations and backfills are the scariest thing your team ships. Datapace dry-runs them against a production-shaped clone, estimates runtime and lock footprint, and rewrites them into safe batched patterns when the original would hurt.

Dry run accuracy

±10%

Runtime estimate

vs real clone

Batched pattern

auto generated

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The problem

You need to update 400 million rows. You run it in one statement. The table locks for 8 hours. Writes queue up. Customers churn.

The fix was to batch by primary key cursor, 50,000 rows at a time, with a short pause between batches. But nobody on the team knew that pattern by heart, or they knew it but did not feel like writing it by hand for every one-off script.

Most one-off scripts run once and disappear. You have no way to catch the bad patterns before they execute because there is no review process for "ad hoc operational scripts".

How Datapace solves this

The fix, automated.

01

Dry runs the script against a schema clone

Paste your migration or backfill into the Datapace dashboard, or tag the PR that contains it. Datapace runs the statement on a schema clone with live row counts and returns the execution plan, expected runtime, lock footprint, and bloat impact. You see the cost before you touch prod.

dry-run · against cloneunsafe for production
pastemigrations/backfill_read.sql

UPDATE messages

SET read = true

WHERE created_at < now() - interval '30 days';

runtime

8h 12m

lock type

ACCESS EXCLUSIVE

rows rewritten

420M

bloat produced

~180 GB

02

Flags lock and bloat risks ahead of time

Single transaction UPDATE statements on large tables trigger full table rewrites and leave hundreds of gigabytes of bloat. Datapace flags these before you run them, names the specific risk (lock duration, rows rewritten, bloat produced, invalidated indexes), and explains what will break if you ship the original.

execution timelinemessages table
Single transaction8h 12m locked
writes blocked for entire window
Batched cursor45 min · no lock

8,400 batches · 100ms sleep · safe during business hours

Zero blocked writes. Same data result, delivered without a maintenance window.

03

Generates a batched alternative

For unsafe scripts, Datapace generates the safe version: cursor based batching, commit per chunk, optional sleep between batches, progress logging. The alternative includes an updated runtime estimate so you know whether to run it in a maintenance window or during normal hours. Every proposed alternative is also checked against your live workload, so the rewrite does not create new contention or plan regressions elsewhere.

datapace · safe rewritegenerated
-- batched backfill · cursor based
DECLARE cur CURSOR FOR
SELECT id FROM messages
WHERE created_at < now() - interval '30 days'
ORDER BY id;
 
LOOP
FETCH 50000 FROM cur INTO batch;
UPDATE messages SET read = true
WHERE id = ANY(batch);
COMMIT;
PERFORM pg_sleep(0.1);
END LOOP;

batch

50,000

runtime

~45 min

lock

none

Who this is for

Teams that run data migrations, backfills, or cleanup scripts on large tables
Platform teams who get asked to "just run this UPDATE real quick"
Anyone who has considered running a 400 million row UPDATE in a single transaction
Engineers handling GDPR or SOC2 data purges on production volumes

Example workflow

See it in action.

Stop regressions before they ship.

2-minute setup. Read-only Postgres connection. Results delivered in your repo and Slack.

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