Databases
Keep your database fast as your data grows
We choose the right engine, design the schema, and tune queries and indexes so pages stay fast at ten times today's data.
We'll reply with what's causing them and how we'd fix them.
Sound familiar?
- 01
Queries that took milliseconds now take seconds, and they get slower every month.
- 02
The database server keeps asking for more memory and CPU, but performance stays the same.
- 03
Nobody knows which indexes exist, which are used, or which are missing.
- 04
Schema changes are applied by hand, and staging no longer matches production.
- 05
A migration once locked a production table, and the team still talks about it.
- 06
The database was chosen because the team knew it, and now the data model fights it every day.
- 07
Reports run against the production database and slow the app down for customers.
The cost of waiting
Bigger servers won't fix this
Adding memory and CPU hides a slow query for a few months. Then the data grows past the new limit, and you're paying for a larger server with the same problem. Most database slowdowns come from queries, indexes, and schema design, and those don't improve with hardware.
Our approach
How we approach it
Choosing the right database
Transactional records, search, analytics, caching, time-series data, and event streams each have engines built for them. We look at how your data is written, read, and related, how fast it grows, and how often its shape changes. Sometimes the answer is one relational database set up well. Sometimes it's a relational database plus a cache and a search index. We don't add databases you'll have to maintain without a reason.
Fixing performance at volume
A structure that works with a hundred thousand rows can fail at a hundred million. These are the fixes we make most often:
- Rewriting queries around how the database executes them (full table scans, N+1 queries, unbounded joins)
- Adding missing indexes and removing duplicate or unused ones that waste memory and slow writes
- Partitioning or archiving large tables
- Moving read-heavy and reporting workloads to replicas or caches
- Tuning connection pools so they hold up under load
Changing the schema safely
Your product will change, and the schema has to change with it. Every schema change is recorded, versioned, reviewed, and applied the same way in every environment. For products whose data model changes often, we set up progressive schema changes: backward-compatible migrations, expand-and-contract changes, and rollouts without downtime.
Before and after
Before
After
- Before: Slow pages, and you're unsure why
- After: Each slow query is measured, explained, and fixed
- Before: Bigger servers every few months
- After: Memory and CPU used by the queries that need them
- Before: Schema changes run by hand
- After: Versioned migrations run by the pipeline
- Before: Migrations scheduled at 2 a.m. "just in case"
- After: Changes that roll out while the app keeps running
Deliverables
What you get
- A database recommendation with written reasoning
- Schema design and data model documentation
- A query and index audit with measured before-and-after timings
- A version-controlled migration process across development, staging, and production
- Backup, restore, and monitoring setup
FAQ
Questions teams ask before hiring us
01Can you fix performance without changing our database?
Usually, yes. Most gains come from queries, indexes, and schema. We recommend a different engine only when the data model needs it.
02Will a migration take our app offline?
We plan migrations so the app keeps running. Where a short window can't be avoided, we tell you in advance and plan it with you.
Next step
Is your database slowing down?
Send us your five slowest queries. We'll tell you what's causing them.