Technology
PostgreSQL Testing& Development
Postgres enforces a great deal if you let it, and applications frequently assume rules the schema does not actually hold. We check where integrity is really enforced, rehearse migrations at production-shaped volume with reconciliation either side, and profile the queries that will slow down at ten times today's data.
Constraint, key and cascade behaviour verified in the database
Migration dry runs with row counts and checksums
Transaction isolation and deadlock behaviour under concurrency
Query plans and index review before volume makes it urgent
- Best fit
- Products where data correctness matters as much as application behaviour
- Strength
- Constraints, transactions and a type system that can enforce real rules
- Typical first work
- Migration dry runs and integrity checks before a release
- Honest limits
- A database cannot enforce a rule nobody has written down
Self-check
Signs your team needs this
If more than one of these is true, it is usually cheaper to fix now than after the next release.
Migrations are applied to production without a rehearsal at real scale
Data validation in CI compares row counts and stops there
Business rules live in application code but not in the schema
Queries are fast in staging and slow in production
A Senior Engineer replies within one business day. NDA first.
Testing the database, not just through it
Most test suites touch PostgreSQL only as a side effect: a form is submitted, a row appears, the test passes.
Most test suites touch PostgreSQL only as a side effect: a form is submitted, a row appears, the test passes. That verifies the happy path through the application and almost nothing about the data. It will not catch a constraint that was never added, a migration that silently drops a column on a table with production-shaped data, or a query that is fast against a thousand rows and unusable against ten million.
We test the database as its own layer. Constraint and integrity validation, so the rules your product depends on are enforced where they cannot be bypassed. Transaction behaviour under concurrency, because the interesting bugs live in the interleaving. And query performance measured against realistic volumes rather than seed data.
Migrations are the highest-risk change you ship
A migration runs once, in production, usually under time pressure, and frequently with no rehearsal.
A migration runs once, in production, usually under time pressure, and frequently with no rehearsal. We run them as dry runs first: against a restored copy at production scale, timed, with locking behaviour observed and a rollback path proven rather than assumed. Whether an ALTER takes a lock that stalls writes for four minutes is something you want to learn on a copy.
This work sits close to our broader database Testing and ETL and data Testing practices, and it is the same discipline applied to a different layer.
Row counts are not validation
A count that matches proves that the same number of rows arrived.
A count that matches proves that the same number of rows arrived. It says nothing about whether the values are right, the types survived, the nulls landed where they should, or the referential integrity held. We check the content: schema conformance, value-level reconciliation against source, null and boundary handling, and the constraints that should have rejected bad rows in the first place. There is a longer write-up of this argument if it is a conversation you are having internally.
Engagement path
How the engagement runs
How a PostgreSQL engagement runs from first call to handover.
Map the data contract
What the schema promises, which rules are enforced by constraints and which only by convention, and where the gaps are.
Build validation at value level
Reconciliation against source, schema conformance and boundary handling, rather than counts.
Rehearse the migrations
Dry runs at production scale with timing, locking behaviour and a proven rollback path.
Wire it into CI
The checks run on every change, so a regression in the data layer surfaces the way an application regression does.
Deliverables
What you get
Artefacts you keep and can run without us. Everything lives in your repositories and your pipelines.
Handover pack
5 artefacts · yours to keep
A written data contract: what the schema enforces and what it does not
Value-level reconciliation suites rather than row counts
Migration dry-run results with timings and locking behaviour
Constraint and integrity gaps documented with recommended fixes
Query performance baselines at realistic data volumes
Questions
Frequently Asked Questions
Straight answers, written the way we'd say them on a call.
Still curious? Talk to usKeep reading
Where to go next
Teams evaluating PostgreSQL usually read these next.
Need PostgreSQL Expertise?
Start with a scoping call or a free assessment, Engineers available within days.
- A Senior Engineer replies, not a sales layer
- Within one business day, every time
- NDA available before you share any details
16+
Years QA leadership
The founder's enterprise QA career across OTT, SaaS, e-commerce and regulated utilities. Not a team total.
17
Testing disciplines
Each one has its own page, scope and deliverables. Counted from that list, never typed by hand.
6
Markets served
Availability, not delivery history. Each market's page says plainly where we have clients and where we do not.
1
Business day to reply
A Senior Engineer answers, not an autoresponder or a scheduler.
Tell us where quality hurts
Prefer to talk? Book a 30-minute call