Workload capture and ranking
Production query statistics ranked by total time, so fixes start where they save the most.
The Problem
When the App Gets Slower Every Month as the Data Grows
Database slowdowns creep in. Tables that held thousands of rows now hold millions, queries that were fine at launch scan far more data, and the server works harder every week.
01 · Full table scans
The dashboard query reads every order row on each view.
A targeted index and a rewrite let it read only the rows it needs.
02 · N+1 queries
One list page fires hundreds of small queries.
Eager loading and batched queries in the app code cut the round trips.
03 · Connection pileups
Requests time out at peak while connections queue up.
Connection pooling with PgBouncer or the app's own pool keeps connections in check.
04 · Bigger servers
Upgrading the instance raised the bill, not the speed.
Tuning comes first, so you size servers on measured load.
Your app felt fast at launch. Two years later, the orders table holds millions of rows, and the dashboard query scans all of them on every page view. The ORM fires 300 small queries to render one list. Connections pile up at peak hours until requests time out. Someone doubled the instance size last quarter, and the bill went up while the slowness came back. Nobody knows which queries matter most, because nobody measures them.
We start by measuring, not guessing. We capture the real workload with pg_stat_statements or the MySQL slow query log and rank queries by total time. Then we read each plan, fix indexes, rewrite heavy queries, remove N+1 patterns, and tune memory and connection pooling. Every change is tested on a staging copy and shipped as a reversible migration. Alerts catch the next slow query before your customers do.
Real workload, measured
Queries ranked by total time from your production statistics, not from guesses or vendor benchmarks.
Plans read, then fixed
EXPLAIN ANALYZE shows where each query spends its time before we touch an index.
Alerts on slow queries
Slow queries trigger alerts around the clock, so regressions surface before customers complain.
Our Database Optimization Services Process
From Slow Query Review to a Faster Database in Five Steps
You see the ranked query list, each plan, and before and after timings from a staging copy before any change reaches production.
We look at your slowest endpoints, your database version, and its current statistics, then point to the likely causes. You get a short findings list and a straight answer if one index would fix it.
What's Included
What You Get With Our Database Tuning and Optimization
Each engagement measures first and fixes in order of impact. Most include these six parts, from workload capture to the alerts that keep the database fast.
Compare Options
DeveloperLook vs Bigger Server vs In-House Developer
A bigger server buys time fast, and an in-house developer knows the code best. Here is how each handles a database that slows down as it grows.
| Feature | DeveloperLookBest fit | Bigger server | In-house developer |
|---|---|---|---|
| First step | Measure the real workload | Pick a larger instance | Check the obvious query |
| Root cause | Found in query plans | Left in place | Found if time allows |
| Speed of relief | 1 to 2 weeks | Same day | Depends on priorities |
| Monthly hosting cost | Sized on measured load | Rises with each upgrade | Stays the same |
| App code fixes | ORM and query rewrites | Yes, in their own code | |
| Testing | Staging replay with timings | Not part of it | Varies by team |
| Monitoring | Slow-query alerts set up | Provider metrics only | If someone sets it up |
| Cost | Fixed price from $700 | Higher monthly bill | Full-time salary |
DeveloperLook
Bigger server
- First step
- DeveloperLook: Measure the real workloadBigger server: Pick a larger instance
- Root cause
- DeveloperLook: Found in query plansBigger server: Left in place
- Speed of relief
- DeveloperLook: 1 to 2 weeksBigger server: Same day
- Monthly hosting cost
- DeveloperLook: Sized on measured loadBigger server: Rises with each upgrade
- App code fixes
- DeveloperLook: ORM and query rewritesBigger server:
- Testing
- DeveloperLook: Staging replay with timingsBigger server: Not part of it
- Monitoring
- DeveloperLook: Slow-query alerts set upBigger server: Provider metrics only
- Cost
- DeveloperLook: Fixed price from $700Bigger server: Higher monthly bill
Projects We've Built
Busy Apps We Have Built
Food delivery, tour booking, travel, and store admin apps from our portfolio. None was a tuning project, but each depends on fast queries as orders and users grow.
ZapEats Restaurant Food Delivery App Design & Development
- Food & Beverage
- Food Delivery
- Dashboard
NextWay Tour Booking App and Operator Dashboard
- Travel
- Vacation Rental
- Booking System
Xinomin Fashion Ecommerce Website and Admin Dashboard
- Fashion
- E-commerce
- Dashboard
HoliNest Travel Booking Website and Dashboard
- Travel
- Vacation Rental
- Booking System
What Our Clients Say
What Clients Say After Launch
Feedback from teams we have built fast, data-heavy web apps for.
We had a pretty specific idea of what we wanted our website to become, but I wasn’t sure how easily we could explain all of it to a development team. There were quite a few moving parts, and we were working toward a deadline, so I expected a few things to get lost along the way. That never really happened. They understood what we were trying to achieve, kept us updated throughout the process, and got everything ready within the agreed timeline. The final site feels much easier to navigate, works beautifully on mobile, and is noticeably smoother for our customers. It was a huge relief seeing the original idea actually turn into the website we had in mind.
The mobile experience is probably my favourite part of the new site. We had spent a lot of time making sure the desktop version looked right, and the team kept pushing us to think about how everything would actually feel on a phone too. They were right. The navigation is clean, the interactions feel natural, and everything we’ve tested so far works exactly as it should. They also went through the links, forms, integrations, and other details more than once before launch, which I really appreciated. And even after going live, we could still reach out when something came up. The whole process felt friendly, organised, and surprisingly straightforward.
What I appreciate most is that the website is actually easy for us to manage now. We can update content ourselves instead of sending a developer a message every time we need to change something small. They also paid attention to the technical SEO side, which mattered to us because we didn’t want a new website to create problems for the traffic we already had. I’ve probably asked more questions than I should have since launch, but every question has been handled patiently and without any fuss. The team is easy to work with, they explain things clearly, and when we need something changed, they focus on getting it done rather than making the process complicated.
1,250+
Projects shipped
10+
Years of experience
Top 3%
Upwork Top Rated Plus
5 stars
Average review score
Want results like these?
Tell us what you are building. You get a reply within 24 hours on business days, then a written estimate.
Work Culture
Why Engineering Teams Trust Us With Production Databases
Tuning touches the system your whole product depends on. These habits keep changes measured, reversible, and explained to the engineers who maintain them.
One index before a project
If one index or a single query rewrite fixes the problem, we'll tell you before we quote. Not every slowdown needs a full engagement.
Measure before and after
Every change comes with timings from before and after, taken on the same data. You see what each fix did instead of trusting a feeling.
Reversible by default
Indexes and settings ship as migrations with a rollback path. If a change misbehaves under real load, undoing it takes minutes.
Careful with production
Index builds run concurrently or off-peak, and nothing heavy runs during your busy hours. Your users shouldn't notice we were there.
Engineers learn the why
We walk your developers through each plan and fix. The next slow query gets caught in code review instead of in production.
Access kept to a minimum
We work with read-only access until a change is approved, and credentials stay in your vault. Your data stays inside your environment.
Overview
What do database optimization services include?
DeveloperLook provides database optimization services for PostgreSQL and MySQL databases behind web apps and SaaS products. We capture the real query workload, fix the slowest queries with indexes and rewrites, tune memory and connection settings, and set up slow-query alerts. Projects start at $700, take 1 to 6 weeks, and every change ships as a reversible migration.
DEVELOPERLOOK
Project facts · Database Optimization Services
- Service
- Database Optimization Services (query tuning, indexing, configuration, monitoring)
- Typical timeline
- 1 to 2 weeks for a query tune-up, 3 to 6 weeks for deeper work
- Platforms
- PostgreSQL, MySQL, MariaDB, Supabase, Amazon RDS, Google Cloud SQL, and Azure Database
- Built with
- pg_stat_statements, EXPLAIN ANALYZE, the MySQL slow query log, PgBouncer, Redis, and Grafana
- Experience
- 10+ years of development experience and 1,250+ shipped projects
- Post-launch support
- 30, 45, or 60 days, depending on plan
- Communication
- Calls in US, UK, and AU business hours
- Starting price
- From $700 USD, fixed scope after a free performance review
Reviewed 22 Oct 2026 by Saimul Islam
Good fit
SaaS teams with slowing dashboards
Your app's dashboard took a second to load last year and now takes eight, and customers have started mentioning it on calls.
Teams with database CPU maxed out
Your database CPU sits near its limit at peak hours, and the only fix anyone has tried is upgrading to a bigger instance.
Rails, Laravel, or Django apps
Your ORM fires hundreds of small queries per page, and you suspect N+1 patterns, but nobody has had time for DB performance tuning.
Teams before a traffic peak
You expect a launch or seasonal peak and want database performance optimization done before real users hit the slow paths.
Agencies needing database optimization consultants
Your agency's client app is slow, and you need specialists who can tune its database quietly behind your brand.
Not a fit
The data model is wrong
Your schema itself is the problem, with data duplicated across tables and no keys. Our Database Development Services page redesigns it instead of tuning around it.
Slow warehouse reports
Your slow queries run in Snowflake or BigQuery reports, not an app database. Our Data Warehouse Consulting Services page covers warehouse tuning and costs.
Server upkeep, not queries
You need patching, backups, and uptime care for the server itself rather than query work. Our Server Management Services page covers that upkeep.
Budget under $700
You have one slow query, and your budget is under $700. Running EXPLAIN and adding the index it points to may solve it, and we'll tell you before we quote.
Not sure we're the right fit?
Book a free call or message us. We'll tell you honestly whether we're the right team.
Pricing
Transparent Starting Prices for Database Optimization Services
These are starting points in USD. Your final price depends on database size, query count, and the app code involved, and you get a fixed proposal after a free performance review.
For apps with a handful of slow pages on one PostgreSQL or MySQL database.
$700one-time, USD
- Free performance review
- Workload capture on one database
- Top 20 slowest queries fixed
- Index review with before and after timings
- Slow-query alerts set up
- 30 days of post-launch support
Recommended
For apps where slow queries, ORM patterns, and settings all play a part.
$1,900one-time, USD
- Everything in Query Tune-Up
- N+1 and ORM fixes in your app code
- Memory, autovacuum, or buffer pool tuning
- Connection pooling setup
- Load replay on a staging copy
- 45 days of post-launch support
For products preparing for a launch, a seasonal peak, or much larger data volumes.
$4,400one-time, USD
- Everything in Performance Overhaul
- Read replica for reporting traffic
- Partitioning for up to 3 large tables
- Redis caching for hot queries
- Capacity plan for your expected peak
- 60 days of post-launch support
For Agencies
White-Label Database Optimization Consultants for Agencies
You own the client relationship. We supply the database tuning behind it: workload capture, query and index fixes, configuration, and monitoring on PostgreSQL or MySQL, delivered under your brand. Fixed quotes protect your margin.
How the partnership works
White label: your client only ever sees your brand
- Your client
- You, the agency
- DeveloperLook
Share the slow pages
Send the client's slow endpoints, database version, and read-only access.
- Client needs
- You share the details
- Details received
We measure and price
You get the ranked query list and a fixed quote with dates.
- Scope and plan
- Proposal to resell
- Your quoteYOUR LOGO
Fix and hand off
Fixes, alerts, and a tuning report delivered under your agency's brand.
- Done by our team
- Your brand on it
- Handed to your clientDone
Partner with DeveloperLookDelivered under your brand
Stay client-facing
Your brand on every report and recommendation, and we stay invisible.
Fixed-price tune-ups
Tuning priced upfront, so your client's budget holds.
Read-only first
We start with read-only access to each client database.
Clear tuning reports
Before and after timings your client's developers can verify themselves.
The Right Technology for Your Project
Technology Stack
We tune open databases on the major managed clouds, using each engine's own statistics and the app frameworks your team already runs.
PostgreSQL
MySQL- MariaDB
Supabase
- Amazon RDS
- Google Cloud SQL
- Azure Database
DigitalOcean
- pg_stat_statements
- EXPLAIN ANALYZE
- MySQL slow query log
- Grafana
- Prometheus
- PgBouncer
- Redis
Node.js
Laravel
Django- Ruby on Rails
FAQ
Frequently Asked Questions
Straight answers on what database optimization means, costs, timelines, tuning settings, and speeding up SQL queries.
Saimul IslamFounder & CEO, DeveloperLookStill have questions?
Send a message or book a call with the team.
Database optimization is the work of making a database answer queries faster while using less CPU, memory, and disk. It covers indexes, query design, configuration, connection handling, and sometimes the schema. The goal is a database that keeps up as data and users grow, without simply buying a bigger server.
In practice, it means finding the few queries that consume most of the database's time and making them cheaper. The work: ranking queries by total time, reading their plans, adding the right indexes, rewriting a few joins, and fixing app code that sends too many small queries. Most of the gains come from a short list.
Our database optimization services start at $700 for workload capture and fixes to the top 20 slowest queries on one database. A performance overhaul with ORM fixes, settings, and pooling starts at $1,900. Scale readiness with a read replica, partitioning, and caching starts at $4,400. Hosting costs stay with your cloud provider.
A query tune-up takes 1 to 2 weeks, and deeper work with app fixes, settings, and load testing takes 3 to 6 weeks. Capturing a representative workload takes a few days, so we turn on statistics on day one. Index builds on large tables are scheduled off-peak, which can add a day.
Database tuning is adjusting a database's settings and structures to fit its actual workload. That includes memory, such as PostgreSQL's shared_buffers and work_mem or MySQL's innodb_buffer_pool_size, plus autovacuum behavior, connection limits, and indexes. Default settings suit a small test server, not a busy production one.
Database performance tuning is the measured process of finding and removing what slows a database down. It starts with statistics on real queries, then moves through plans, indexes, rewrites, and configuration, checking timings after each change. Unlike a one-off fix, it ends with monitoring, so new slow queries show up early.
Measure first: turn on pg_stat_statements or the MySQL slow query log and rank queries by total time. Fix the top few with indexes or rewrites, remove N+1 queries in the app, then tune memory and add connection pooling. Recheck the ranking after each change, because fixing one query often reveals the next.
Query optimization is choosing the fastest way to run a SQL query. The database's planner does part of it automatically, picking join orders and indexes from table statistics. Developers do the rest by writing queries the planner can serve well: filtering early, avoiding functions on indexed columns, and selecting only needed columns.
Run EXPLAIN ANALYZE on the query and look for sequential scans on large tables, row estimates far from reality, and expensive sorts. Add an index that matches the filter and sort order, rewrite correlated subqueries as joins, and use keyset pagination instead of large offsets. Then run it again and compare timings.
Start with the plan, not the query text. A missing or unused index causes most of the slow SQL queries we see, followed by large offsets, leading wildcard searches, and stale table statistics. Fixing those, and running ANALYZE so the planner has fresh statistics, speeds up most queries without touching the server.
Saimul IslamFounder & CEO, DeveloperLookStill have questions?
Send a message or book a call with the team.
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