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Centricone Technologies
Data

PostgreSQL consulting for databases that outgrew their original design

Centricone tunes, scales, and migrates PostgreSQL: query plans and indexes, replication and failover, major-version upgrades, and moves off commercial engines.

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What we build

What we build with PostgreSQL

Query and index work with evidence

Plans read, indexes chosen against real workload, and before-and-after numbers recorded — not a list of recommended settings.

Replication, failover, and read scaling

Streaming replicas, connection pooling that actually holds under load, and failover exercised rather than assumed.

Migrations onto Postgres

Oracle and SQL Server moves with schema translation, data verification, and a rollback path — plus honesty about the stored-procedure work nobody enjoys.

When PostgreSQL is the right call — and when it is not

We would rather talk you out of a stack than deliver the wrong one well.

Reach for it when

  • Transactional workloads that need real integrity guarantees
  • Teams wanting to reduce commercial database licensing
  • Mixed workloads: relational, JSON documents, full-text search, and vectors in one engine

Pick something else when

  • Very large analytical workloads better served by a warehouse like Snowflake or BigQuery
  • Workloads locked to vendor-specific features with no viable equivalent
  • Teams unwilling to run connection pooling — Postgres punishes that at scale

What we normally run alongside it

No stack is one tool. These are the pieces that usually show up with PostgreSQL on our projects.

  • pgBouncer
  • TimescaleDB
  • pgvector
  • Debezium
  • Flyway

PostgreSQL questions we get asked

Weighing it against something else? Tell us the constraints and we’ll give you a straight recommendation.

For most transactional applications, yes, and the licence saving is often the business case on its own. The work is in stored procedures, vendor-specific SQL, and features like partitioning that behave differently. We size that honestly before recommending a move.
Usually plans changing as statistics shift, indexes that stopped matching the query pattern, table bloat from update-heavy workloads, or connection exhaustion. All four are diagnosable and all four are fixable without changing the application.
Almost always, once you have more than a modest number of clients. Each Postgres connection is a process; a few hundred will hurt. pgBouncer in front is one of the highest-value changes available on most installations.
PostgreSQL for most new systems. It is stricter about data correctness, has substantially better support for JSON, window functions, and complex queries, and its extension ecosystem covers ground MySQL does not. MySQL remains a reasonable choice where a team knows it well or a platform mandates it.
Continuous archiving with point-in-time recovery, so you can restore to a moment rather than to last night. The part that matters more than the configuration is rehearsal: a backup nobody has restored is a hypothesis, so we test the restore on a schedule and record how long it actually takes.
Far larger than most teams need — multi-terabyte instances are routine. Problems show up as individual tables grow, and the fix is usually partitioning by time or tenant plus archiving what is never read, rather than a move to a different database.

Keep reading

Database Management

The capability page behind this technology — how we scope, build, and support work like this.

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Industries we use it in