Pakistan

Database Design Services

Database problems are usually decided on day one, discovered on month six

Most slow, awkward databases weren't built by careless engineers - they were designed around the data as it looked at launch, without enough thought for how the application would actually query it once real usage patterns emerged. Database design work is where we think through those query patterns upfront: what gets read often, what gets written often, and which relationships actually need to be fast versus which can afford to be slower.

What's included

Schema design for MongoDB (document-based) or PostgreSQL/MySQL (relational), chosen based on how your data is actually shaped - not a default preference
Indexing strategy matched to your real query patterns, not indexing everything (which slows writes) or nothing (which slows reads)
Migration planning if you're moving from an existing database or spreadsheet-based system
Backup and recovery strategy appropriate to how critical the data is

Our process

1. Map real query patterns

We ask what the application actually needs to look up, filter and sort - not just what data exists, but how it gets used - before designing the schema around it.

2. Design and review

A written schema document you can review before we build against it, catching mismatches with business logic early.

3. Build with realistic test data

Schemas get tested against data volumes resembling your real future scale, not a handful of sample rows that hide performance problems until you have real users.

4. Migration (if applicable)

Existing data gets migrated with validation checks, not a blind bulk import that silently drops or corrupts edge cases.

When this matters most

Applications expecting real growth in data volume, or already experiencing slow queries as an existing system scales, get the most value here. A brand-new MVP with a handful of users usually doesn't need deep schema optimization yet - we'll say so rather than over-engineer a database for scale you don't have.

Pricing

Rs 50,000-250,000 depending on schema complexity and whether it includes migrating existing data.

MERN Stack Development · Cloud Migration · Hire Software Developers · All services

Frequently asked questions

MongoDB or a relational database - which do we need?

Depends on how your data relates - MongoDB suits flexible, document-shaped data; PostgreSQL/MySQL suit data with strict relationships and complex joins. We recommend based on your actual data model, not a default preference.

Our app is already slow - can you fix an existing database?

Yes - we audit real query patterns first to find what's actually causing slowness, which is often a missing index rather than a full schema rewrite.

Do we need this for a brand-new project?

Only if you're expecting significant scale soon - a new MVP with few users usually doesn't need deep optimization yet, and we'll tell you that directly rather than over-engineer it.

Can you migrate data from spreadsheets?

Yes, with validation checks to catch the edge cases a blind bulk import would silently corrupt or drop.

How do you decide on indexing?

Based on your real query patterns - what gets filtered, sorted or looked up often - rather than indexing everything, which slows down writes unnecessarily.

What does it cost?

Rs 50,000-250,000 depending on schema complexity and whether existing data migration is included.

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