Database design that does not become the thing slowing you down

Slow applications usually slow down at the database. Queries that were fine with a little data struggle with a lot of it, and the structure gets harder to change every month.

We design databases that hold up and fix the ones that do not, in PostgreSQL, MySQL and MongoDB. For businesses in Colorado and across the US.

An engineer working at a computer in a data center

99+projects completed

8+years of experience

150%average business growth

99%success rate

What our database development covers

  • Schema design

    How data is structured and related, decided before the application is built on top of it.

  • Query optimization

    Finding the expensive queries and fixing them, usually with indexes and sometimes with a new structure.

  • Migrations

    Moving between database systems, or restructuring one, without losing data or long downtime.

  • Caching

    Redis for data that is read often and changes rarely.

  • Data integrity

    Constraints, transactions and validation, so bad data is rejected at the door.

  • Backup and recovery

    Backups that are tested, so recovery is proven instead of assumed.

Signs the database is the problem

  • Pages got slower as you got busier. Queries that were fast at launch do not scale with your data.
  • Reports take minutes. Repeated work that could be cached, or a missing index.
  • The same data lives in several places. The copies drift apart and nobody knows which one is right.
  • Adding a field needs a developer and a release. The schema was built around old requirements, not the shape of the data.
  • Nobody has tested a restore. Backups that have never been restored are a hope, not a plan.
Schema designQuery optimizationTested backups

The stack we build with

PostgreSQL (including advanced indexing and partitioning), MySQL, MongoDB, Redis and DynamoDB, with Prisma, TypeORM or Mongoose, and execution plan reviews for every slow query. The database should follow the shape of your data, not the other way round.

How a database project runs

  1. Measure firstQuery logs show which queries take the most time. No guessing.
  2. Model the dataNew builds start with entities and relationships, agreed before any app code depends on them.
  3. Index and optimizeTargeted changes, measured before and after.
  4. Add caching where it earns its placeAfter the query work, so the cache does not hide the real problem.
  5. Document and monitorThe schema is written up and slow queries are watched, so regressions show up early.

Why businesses choose us for database work

  • We measure before changing anything. Findings come from your query logs.
  • Results are shown, not claimed. Before and after numbers for every change.
  • Backups are tested. Restores are proven before an incident tests them for you.
  • We say when it is not the database. Sometimes the slowdown is elsewhere, and we will not bill you for the wrong fix.

Keep exploring

IT & Development

12 more ways we build. One small team covers the interface, the server, the data and the cloud.

How a project runs, from brief to launch.

  1. Step 1, day 1

    Tell us what you need

    Describe the problem or the product through the contact form. A rough idea is enough.

  2. Step 2, discovery

    We map it and quote

    We look at what exists, agree the scope in writing and give you a quote before any build starts.

  3. Step 3, the build

    Short cycles you can review

    You talk to the engineers doing the work and see progress at the end of every cycle.

  4. Step 4, launch

    Launch and hand over

    We deploy, monitor the first weeks and hand over documentation your team can use.

Questions about database development

Still unsure? Send us a rough brief and we will tell you what it involves and whether it is worth building.

Why did our application get slower over time?

Usually because some queries do not scale. They were fast with little data and slow with a lot of it. Indexes and query structure explain most cases.

Can you fix performance without a rebuild?

Usually, yes. Most gains come from a handful of indexes and rewritten queries, not from starting over.

Which database should we use?

The one that fits your data. Related records with strict rules suit PostgreSQL or MySQL. Flexible documents can suit MongoDB. We will recommend one after seeing the data.

Do you handle migrations between database systems?

Yes, in stages with checks at each step, so no data is lost and downtime stays short.

Are our backups actually working?

The only way to know is to restore one. We test restores as part of the work.

Contact us

Tell us what got slow

Describe the slow part of the application and roughly how much data you have. We will tell you whether the database is the problem and what fixing it involves.

Prefer to talk?(240) 332-1637support@rizingmetrics.com

A small business team working together in an office