Data & AI
PostgreSQL: design, optimization, replication and migration
PostgreSQL is the relational engine we recommend by default for business applications, SaaS products and APIs: reliable transactions, rich types (JSONB, arrays, ranges), window functions, extensions such as PostGIS or pgvector, and predictable behavior under load.
This service covers the whole life cycle of a PostgreSQL database: schema design, query and configuration optimization, replication setup, major version upgrades, migration from MySQL, Oracle or SQL Server, and operation on Amazon RDS or Aurora. It is for teams that already run PostgreSQL in production as well as those who want to move to it.
We work with PostgreSQL's native tools: EXPLAIN ANALYZE for execution plans, pg_stat_statements to identify expensive queries, logical replication for migrations without downtime, PgBouncer for connection pooling, and a properly tuned autovacuum to prevent table bloat.
When do we step in?
Slow database despite a powerful server
The server has memory and cores, yet queries remain slow. Often the configuration is still the default (shared_buffers, work_mem), the indexes do not match the queries, or autovacuum cannot keep up with the write rate.
Migration to PostgreSQL from another engine
You are leaving MySQL, Oracle or SQL Server for cost, feature or licensing reasons. Types, sequences, stored procedures and SQL behavior differences need to be handled methodically.
Overdue major version upgrade
Your database runs on a version that is no longer maintained. A major upgrade needs a plan: pg_upgrade or logical replication, extension tests, application checks, a cutover window.
Too many connections, saturation
Every application instance opens its own connections and the database hits its limit. A properly sized connection pool, with PgBouncer or on the application side, usually solves the problem.
Need for replication and failover
You need a replica for reads, disaster recovery or reporting, without slowing down the primary. Physical and logical replication are configured differently depending on the goal.
How we work
- 1
Diagnosis
We analyze the configuration, pg_stat_statements data, unused or missing indexes, vacuum state and logs. We produce a list of actions prioritized by impact.
- 2
Schema design or correction
Appropriate types, constraints, foreign keys, partial or composite indexes, declarative partitioning for large historical tables. Changes are delivered as versioned migrations.
- 3
Optimization
Rewriting expensive queries, tuning memory and autovacuum parameters, setting up PgBouncer, checking execution plans after each change.
- 4
Replication, backups and upgrades
Depending on your needs: streaming replica, logical replication, backups with pgBackRest or pg_dump, point-in-time recovery, and a major upgrade plan tested on a copy.
- 5
Migration to PostgreSQL
Schema conversion, data transfer, continuous replication during the transition period, application compatibility tests and a short cutover with a rollback option.
Technologies we use
- PostgreSQL
- Amazon RDS and Aurora PostgreSQL
- PgBouncer
- pgBackRest
- pg_stat_statements
- Logical and streaming replication
- pgvector
- PostGIS
- pgloader
- Flyway and Liquibase
Related expertise
Why choose Agencei?
PostgreSQL every day
We build applications on PostgreSQL and administer it for our clients. We know its real strengths and pitfalls: locks during ALTER TABLE, bloat, plans that change after statistics updates.
Migrations without extended downtime
We use logical replication and short cutovers to migrate or upgrade without a long outage, with a tested rollback plan.
No magic configuration
Every parameter we change is justified by a measurement and verified after deployment. We do not copy configurations found online.
Verified application compatibility
We test your application's ORM, queries and procedures against the new database or the new version before any cutover.
In brief
- What is this service?
- Specialized PostgreSQL service: schema design, optimization, replication, backups, major version upgrades, migration from other engines and operation on Amazon RDS or Aurora.
- Who is it for?
- Technical teams and businesses that run PostgreSQL in production or want to migrate to it from MySQL, Oracle or SQL Server.
- What problem does it solve?
- Slow queries, default configuration, connection saturation, outdated versions, no replica, migration to carry out without downtime.
- How long does it usually take?
- A diagnosis often takes a few days. An optimization or an upgrade takes a few days to a few weeks. A migration from another engine is usually measured in weeks, sometimes months for complex applications.
- What factors influence the price?
- Price depends on volume, the number of databases and environments, schema and stored procedure complexity, availability requirements and the chosen hosting.
- How does the engagement run?
- Measured diagnosis, prioritized action plan, tests on a copy, deployment through versioned migrations or logical replication, verification after cutover.
- What are the risks?
- An untested migration or upgrade can break queries or extensions. Unmeasured configuration changes can make performance worse.
- What alternatives exist?
- Staying on the current engine and optimizing it, moving to a managed service without changing engine, or hiring an in-house PostgreSQL administrator.
Frequently asked questions
Should I choose Amazon RDS or a self-hosted PostgreSQL server?
RDS or Aurora simplify backups, patching and replication, at a higher cost and with a few limits (available extensions, system access). A self-hosted server gives full control but requires real operations work. We advise based on your team and constraints, and we work on both.
How do you migrate from MySQL to PostgreSQL without losing data?
We convert the schema (types, auto-increments, collations), transfer the data with pgloader or a change data capture tool, then compare row counts and samples between both databases. The application is tested on PostgreSQL before the cutover, which remains reversible.
Is a major version upgrade risky?
It is manageable when prepared. We check extension and driver compatibility, test pg_upgrade or logical replication on a copy, and plan a short window. The main risk is postponing it until the version is no longer maintained.
Why do my queries change plans without any code change?
The planner picks a plan based on table statistics. As data evolves, the plan can change. Up-to-date statistics, suitable indexes and sometimes extended statistics stabilize this behavior. We analyze it with EXPLAIN ANALYZE.
Can PostgreSQL be used for AI-related vector search?
Yes, with the pgvector extension. For moderate volumes it avoids adding a dedicated vector database and keeps embeddings next to business data. For very large volumes or complex filtering, we evaluate specialized solutions.
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