Schema & data model design
Relational and document models with the right tables, relationships and constraints for how you'll query.
Backend Development · AI-First · Results-Driven
Databases & Data Modeling,Designed to Last
Short answer: Databases and data modeling are the foundation of a backend: the data model is how you decide what your data is and how the pieces relate, and the database is where it lives and is queried. Good modeling and indexing keep queries fast as records pile into the millions, while a poor schema makes every feature slower and every change risky. We design schemas, tune queries and build data pipelines on both SQL and NoSQL stores so your data stays fast, correct and easy to build on.
Database Design & Data Modeling That Scales
Data modeling is the step where you decide what your application's data actually is — the tables or collections, the fields, and how records relate to each other. The database is the engine that stores and retrieves it. This is the most consequential decision in a backend, because everything else is built on top of it: a clean model makes features easy to add and queries fast, while a tangled one makes every change a risk and every page load slower than it should be.
The choices that matter are the schema shape, indexing, and picking the right store for the job. Proper normalization and foreign keys keep data consistent; the right indexes turn a slow scan into an instant lookup; and choosing SQL versus NoSQL — or both — depends on whether your data is relational, document-shaped or high-write. The classic failures are missing indexes that surface only under real data volume, N+1 query patterns, and a schema that can't answer the questions the business now asks without a painful migration.
We model your data around how the product will actually query it, add indexes and constraints from day one, and write migrations that are safe to run on live data. Where you need to move data between systems, we build pipelines that keep it clean and in sync — so reporting, search and features all read from data you can trust.
What we cover
What We Build in Databases & Data Modeling
Indexing & query tuning
Indexes, query rewrites and execution-plan analysis that turn slow pages into instant ones.
SQL vs NoSQL selection
Choosing PostgreSQL, MongoDB, DynamoDB or a mix based on your data shape and access patterns.
Migrations & versioning
Versioned, reversible schema migrations that run safely against live production data.
Data pipelines & ETL
Pipelines that move, clean and reshape data between systems for reporting, search and features.
Replication, backups & DR
Read replicas, automated backups and recovery plans so data survives failure and stays available.
Services
Database & Data Modeling Services
From a first schema to a tuned, replicated data layer with pipelines feeding it — on the store that fits your data.
New schema design
Design a data model and database from scratch, built around your product's real query patterns.
Database migration
Move data between engines or versions — for example legacy SQL Server to PostgreSQL — with zero data loss.
Query & index optimization
Find and fix the slow queries and missing indexes behind sluggish pages and reports.
Data pipeline & ETL build
Batch or streaming pipelines that sync and transform data between apps, warehouses and search.
NoSQL & caching layer
Add a document store, key-value cache or search index where relational tables aren't the right fit.
Backup, replication & DR
Set up automated backups, read replicas and a tested recovery plan for your database.
Tools & platforms
The Data Stack We Build With
The exact toolset depends on your goals — these are the platforms we use most, and we work with whatever your team already relies on.
Relational Databases
NoSQL & Document Stores
Caching & Search
Pipelines & Warehousing
Chosen per project — not a fixed menu. Have a preferred tool or platform? We’ll work with it.
Built to last
Secure, Accessible & Built to Last
We build on modern, well-supported frameworks with security and accessibility baked in — dependency hygiene, input validation, HTTPS and WCAG-minded UI — so your product is safe and usable from day one.
You own all the code and assets. Everything ships with documentation and a clean handover, so your team (or ours) can maintain and extend it without lock-in.
Who we work with
Industries We Build For
20+ years across sectors — in Houston and internationally.
Transparent pricing
Estimate your project in seconds
Pick what you’re building for an indicative range, then request an exact quote. No email wall.
Simple prices for typical tasks
- API buildfrom $8k
- Backend + DBfrom $15k
- Integrationsfrom $10k
- Care planfrom $800/mo
Proof
700+ projects, 20+ years
See the products and growth work we’ve shipped across industries — and request a case study relevant to yours.
How we work
Fixed scope. Sprints. Working software.
- 01
Scope & fixed estimate
A short discovery call turns your idea into a clear spec and a firm range — free.
- 02
Design & architecture
UX, data model and stack chosen for your scale, not ours.
- 03
Build in sprints
Working software every 1–2 weeks — you see progress, not promises.
- 04
Launch & scale
We ship, measure and keep improving with care plans.
FAQ
Database & Data Modeling questions
How much does database design and data modeling cost?
A schema design or focused optimization engagement typically starts around $5,000, while a full data model with pipelines, migration and a replicated setup can run $25,000 or more. Cost depends on data volume, how many systems are involved, and complexity — use the estimator above, then book a free call for a firm quote.
What is data modeling?
Data modeling is deciding what your application's data is and how it fits together — the tables or collections, the fields, and the relationships between them — before and as you build the database. A good model makes queries fast and features easy; a bad one slows everything down and makes changes risky.
How long does database design take?
An initial schema design for a new product usually takes 1–3 weeks; a database migration or a full pipeline build runs 4–10 weeks depending on data volume and how many systems connect to it. We validate the model against real query patterns before we build on it.
Should I use SQL or NoSQL?
Use SQL (like PostgreSQL) when your data is relational and consistency matters — most business apps. Use NoSQL (like MongoDB or DynamoDB) for document-shaped, high-write or flexible-schema data. Many products use both, and we help you pick per use case rather than forcing one everywhere.
Can you fix a slow database without rebuilding it?
Often, yes. Many performance problems come from missing indexes, N+1 queries or a few bad queries, which we can diagnose and fix without a rewrite. When the schema itself is the bottleneck, we plan a safe, incremental migration rather than a big-bang change.
Can you migrate our existing database to a new system?
Yes. We migrate between engines and versions — for example MySQL to PostgreSQL, or on-prem to cloud-managed — with data-integrity checks, a rollback plan and minimal downtime, keeping the application running throughout.
Do you set up backups and disaster recovery?
Yes. We configure automated backups, point-in-time recovery, read replicas and a documented, tested recovery procedure, so your data survives hardware failure, mistakes and outages.
Do you do database work for clients outside Houston?
Yes. We're based in Houston, TX and handle database design, tuning and migration for clients nationwide and internationally — across 20+ years we've delivered 700+ projects for local and remote teams alike.
Get started with your data model
Book a free consultation — we'll review your data needs and give you an honest range.
Knowledge hub
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