Database design that keeps your application fast
Gjethe designs and optimises databases for applications: data modelling, PostgreSQL, MySQL and MongoDB schemas, indexing and query tuning, safe migrations, moving from spreadsheets or legacy systems, backup and recovery planning, and scaling through read replicas, partitioning or caching. We start from how your application reads and writes data and design the structure around that.
- Free first consultation
- Written quote for your project
- Flexible payment milestones
At a glance
- Databases
- PostgreSQL, MySQL, MongoDB, SQLite, Redis
- Work
- Modelling, indexing, tuning, migrations
- Scale
- Replicas, partitioning, caching
- Safety
- Backups, recovery tests, access control
Definition
What is database design?
Database design is planning how data is structured, related, stored and accessed, so an application stays correct, fast and maintainable as it grows.
Many slow applications aren't slow because of their code. A missing index, a query that loads thousands of rows to show ten, or a schema that forces complicated joins can turn a fast page into a frustrating one, and the problem grows with every new customer. A well-designed database prevents most of these issues, and a careful review can fix many of them in existing systems.
Who is it for?
SaaS products that are growing
Pages that were fast at launch slow down as data grows.
New products
A data model designed properly before code locks it in.
Teams running on spreadsheets
A real database when spreadsheets can no longer keep up.
Legacy systems
Migrating old databases to modern, well-structured ones.
What's included, and what you keep
What's included
- Data modelling and entity design
- Schema design with constraints and relations
- Indexing strategy
- Slow-query analysis and tuning
- ORM query review
- Safe schema migrations
- Data migration from spreadsheets or legacy systems
- Backup, restore and recovery testing
- Access control and roles
- Read replicas, partitioning and caching
- Monitoring and alerting
What you receive
Handed over at the end. Yours to keep.
- Data model diagrams
- Schema and migration scripts
- A performance report with before-and-after measurements
- Backup and recovery runbook
- Documentation of conventions
Model the data around how it's used
A data model should answer the questions your application asks most often, quickly and correctly. We start with the main screens, reports and integrations, list the queries they need, and design tables, relations and indexes for those patterns. Constraints in the database, not only in the code, keep data correct when bugs happen.
Common causes of slow databases
| Cause | Typical fix |
|---|---|
| Missing or wrong indexes | Indexes matched to real query patterns |
| N+1 queries from an ORM | Eager loading or rewritten queries |
| Loading more data than needed | Pagination and selecting only required columns |
| Large tables with old data | Partitioning or archiving |
| Heavy reporting on the main database | Read replicas or a separate analytics store |
| Lock contention | Shorter transactions and better write patterns |
Migrations without downtime
Changing the structure of a live database can lock tables and take an application down. We plan migrations in safe steps: add new columns and tables first, backfill data in batches, switch the application over, then remove the old structure. Each step is reversible and tested on a copy of production data first.
Backups you can trust
Most managed databases take backups automatically, but few teams test restoring them. We set up backups that match how much data you can afford to lose, test restores regularly and write a runbook so anyone on your team can recover the database calmly when it matters.
SQL or NoSQL?
Relational databases like PostgreSQL suit most business applications: structured data, relations, transactions and reporting. Document databases like MongoDB can suit flexible content and certain high-write workloads. Many systems use both, with Redis for caching. We recommend based on your data and queries, not fashion.
Signs your database needs attention
- Pages get slower as you add customers
- Reports time out or lock the application
- Nobody has tested restoring a backup
- Schema changes are scary and done at night
- The same data is stored in several places
- Developers avoid touching certain tables
Multi-tenant SaaS data
SaaS products store many customers' data in one system. Whether each customer gets a separate database, a separate schema or shared tables with a tenant column affects security, performance, cost and how easily you can serve large customers. We help you choose, and implement safeguards such as row-level security so one customer can never see another's data.
Caching without stale data
Caching can make an application dramatically faster, and it can also show users outdated information. We cache what is safe to cache, set clear expiry and invalidation rules, and measure the effect, so speed improves without confusing anyone.
How database design works, step by step
Every step has a clear output you can review. Timing is agreed in your quote.
- 1
Review
Schema, queries, indexes, load and backups analysed.
- 2
Measure
Slow queries and bottlenecks identified with real data.
- 3
Design
Model, indexes and changes proposed with expected effects.
- 4
Implement
Changes applied through safe, reversible migrations.
- 5
Verify
Before-and-after measurements and restore tests.
- 6
Document
Diagrams, runbooks and conventions handed over.
Tools, and what shapes your quote
Pricing is based on your project and agreed in your quote. These are the things that move it.
| Factor | Why it matters |
|---|---|
| Database size | Large datasets take longer to analyse and migrate. |
| Number of applications | Several apps sharing a database need careful coordination. |
| Migration complexity | Moving from legacy systems or spreadsheets needs cleaning and mapping. |
| Downtime constraints | Zero-downtime changes need more careful staging. |
| Access | Direct access to production metrics speeds up analysis. |
| Area | Tools |
|---|---|
| Databases | PostgreSQL, MySQL, MariaDB, MongoDB, SQLite, Redis |
| Analysis | EXPLAIN ANALYZE, pg_stat_statements, Percona tools |
| Migrations and ORMs | Prisma, Drizzle, Django ORM, Laravel migrations, Flyway |
| Managed services | Supabase, Neon, AWS RDS, Google Cloud SQL, PlanetScale |
Common mistakes to avoid
What we see go wrong most often, and how a good project avoids it.
Indexes added by guesswork
Indexes must match real queries; unused ones slow writes.
Constraints only in code
Without database constraints, bugs quietly create bad data.
Untested backups
A backup that can't be restored is no backup.
Big-bang migrations
Large changes in one step risk long locks and difficult rollbacks.
Frequently asked questions
Can you speed up our slow application?
Often, yes. We analyse slow queries and database load, then fix indexes, queries and structure, measuring the effect.
Which databases do you work with?
PostgreSQL most often, plus MySQL, MariaDB, MongoDB, SQLite and Redis.
Can you migrate our data from spreadsheets?
Yes. We design a proper schema, clean and map the data, and import it with checks.
Will migrations cause downtime?
We plan changes in safe steps to avoid or minimise downtime, tested on a copy of production data first.
Do you work with managed databases?
Yes, including Supabase, Neon, AWS RDS, Google Cloud SQL and others.
Can you review our ORM queries?
Yes. ORMs make some inefficient patterns easy, and we find and fix them in your code.
Do you set up backups?
Yes, with regular restore tests and a written recovery runbook.
Do you need access to production?
Read access to metrics and query statistics helps a lot. Changes are tested elsewhere first and applied with your approval.
How is database work priced?
It is quoted on database size, the scope of review or migration and downtime constraints.
Can you add row-level security to our database?
Yes. In PostgreSQL we can enforce tenant and user access rules in the database itself, as an extra safeguard behind your application code.
Can you help us choose a managed database provider?
Yes. We compare options on cost, performance, backups, location and features you need.
Can you clean up duplicate or inconsistent data?
Yes. We find duplicates and inconsistencies, agree rules for resolving them, clean the data and add constraints so it doesn't happen again.
Can you design a database for a new product?
Yes. We model the data from your requirements and screens before development starts, which avoids costly changes later.
Can you help with full-text search?
Yes, using PostgreSQL's built-in search or dedicated tools such as Meilisearch or Elasticsearch where needed.
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Database Design by industry
Make your data fast and safe.
Tell us what you need. You get an honest assessment, a clear plan and a written quote. The first consultation is always free.
- What happens next
- 1You tell us what you need
- 2We aim to reply within 24 hours with questions
- 3You get a written quote for your project