Database Engineering

Database Development Services

Schema design, migrations that don't lose data, and queries that stay fast as the table grows.

Most performance problems that get blamed on the application are database problems: a missing index, an N+1 query, a schema that made sense at 10,000 rows and stopped making sense at 10 million. We work on the storage layer directly — modeling, indexing, migrating, and tuning — rather than papering over it with caching.

We work in Postgres most often, and also MySQL, SQL Server, MongoDB, Redis, ClickHouse, and the managed equivalents on AWS, GCP and Azure. If you are choosing between them, we will tell you which one fits the access pattern you actually have.

What we build

Schema design & modeling

Relational modeling that holds up as requirements change — constraints, keys, and normalization decisions made deliberately rather than inherited.

Migrations

Zero-downtime schema and data migrations, including cross-engine moves, with rollback plans and verification at each step.

Query & index optimization

Profiling real production workloads, then fixing the queries and indexes that account for the cost — measured, not guessed.

Replication & high availability

Read replicas, failover, connection pooling, and backup strategies that have actually been restored from.

Data pipelines

ETL and CDC into warehouses and analytics stores, with schema evolution handled rather than deferred.

Postgres extensions

pgvector for embeddings, PostGIS for geospatial, TimescaleDB for time series — using the database you already run.

How an engagement runs

01

Audit

We profile the live workload — slow query logs, index usage, lock contention, growth curves — and tell you where the cost actually sits.

02

Plan

A written plan naming what changes, in what order, with the risk and rollback for each step. You approve before anything runs.

03

Implement

Changes ship incrementally behind verification, against a restored copy of production first.

04

Operate

Monitoring, alerting, and the runbooks your team needs to own it after we hand it back.

Open-Source Databases

We evaluate and deploy these in production. Browse all 493 guides, or talk to us about a specific tool.

Open-Source Databases

acl

Acl is a mature C/C++ network library and server framework supporting coroutines, HTTP/HTTPS, Redis, MQTT, and database clients across Linux, Windows,…

Open-Source Databases

active_record_doctor

Active Record Doctor is a Ruby gem that automatically detects database design issues in Rails applications—such as missing indexes, foreign key constr…

Open-Source Databases

activerecord-sqlserver-adapter

activerecord-sqlserver-adapter is a Ruby gem that enables Rails applications to use Microsoft SQL Server as their database. It translates Rails' Activ…

Open-Source Databases

Addax

Addax is an open-source ETL tool written in Java that moves data between 20+ SQL and NoSQL databases, Excel, and cloud storage. It evolved from Alibab…

Open-Source Databases

aioway

AioWay is a Python-based optimizing compiler for deep learning that automatically selects and configures ML algorithms based on task and resource cons…

Open-Source Databases

airframe

Airframe is a Scala framework providing dependency injection, serialization, testing, logging, and RPC capabilities for building web and backend appli…

Open-Source Databases

alembic

Alembic is a database migration tool for Python applications using SQLAlchemy. It automates schema changes, supports version control-like workflows fo…

Open-Source Databases

altimate-code

Altimate Code is an open-source TypeScript harness that gives AI agents (Claude, Codex, local LLMs) a deterministic data engineering toolkit with 100+…

Open-Source Databases

Android-Debug-Database

Android Debug Database is a browser-based debugging tool for Android developers to inspect and edit SQLite databases, SharedPreferences, and Room data…

Questions clients ask us

Can you migrate us off a managed service, or onto one?
Both. We have moved teams from RDS to self-hosted Postgres for cost reasons and the other direction for operational ones. The right answer depends on what your team wants to be responsible for at 2am.
Do you work with our existing schema, or rebuild it?
Almost always work with it. A rebuild is occasionally right, but it is a much larger project than most teams expect, and incremental migration usually gets to the same place with far less risk.
How do you handle migrations without downtime?
Expand-and-contract: add the new structure, dual-write, backfill, verify, cut reads over, then remove the old structure. Each step is independently reversible, which is what makes the whole thing safe.
Can you help us choose a vector database?
Often the answer is that you do not need one — pgvector in the Postgres you already run is enough well past the point most teams assume. If you do need a dedicated store, we cover that under AI development services.

Work with a software development company

DEV.co is a software development company with senior engineers across web, data, cloud, and AI development services. Database Engineering work rarely arrives on its own — it comes attached to a product, a migration, or a platform, and we build all three.

Need help with database engineering?

Have a real project conversation with a senior engineer before you commit to an approach.