PostgreSQL Database Experts
Enterprise PostgreSQL consulting, performance tuning, high-availability design, managed-cloud migrations, and long-term stewardship for mission-critical data.
PALADEM’s PostgreSQL database experts help engineering teams design, tune, migrate, and sustain production PostgreSQL environments. Whether you need a version-upgrade plan for a database stuck on an end-of-life release, a performance audit on queries that have grown slower over time, a high-availability redesign, or a measured move from on-prem to a managed cloud service, our PostgreSQL experts deliver work that holds up under real operational scrutiny.
Why PostgreSQL?
PostgreSQL is the most capable open-source relational database available today, and in 2026 it is the default choice for new systems that need serious data integrity, flexible data modeling, and a long operational runway. Its feature breadth is unmatched in the open-source world: JSON and JSONB, full-text search, PostGIS, range and array types, generated columns, logical replication, and a deep extension ecosystem that now includes pgvector for AI and RAG workloads. The permissive license, the track record for reliability, and first-class support on every major cloud make it a safe long-term bet. PostgreSQL rewards teams that invest in operational discipline around autovacuum, indexing strategy, and connection pooling, and it delivers decades of value when it is stewarded well rather than treated as an afterthought.
Our PostgreSQL Services
PostgreSQL Schema & Application Database Development
We design PostgreSQL schemas that fit the real access patterns of your application and make informed use of the features that set Postgres apart: JSONB where semi-structured data genuinely fits, generated columns, partitioning for large tables, and extensions such as PostGIS or pgvector when the workload calls for them. Every schema we ship is architected for the ten-year view, with migration discipline, naming conventions, and indexing decisions documented for the next team that touches it.
PostgreSQL Consulting & Architecture
Our PostgreSQL consulting engagements advise engineering leaders on the decisions that are hardest to reverse: primary-key strategy, partitioning, extension choices, replication topology, connection pooling with PgBouncer in transaction or session mode, and when a workload genuinely needs something beyond a single Postgres cluster. We review existing deployments, identify operational risk, and deliver written recommendations your team can execute, with our database administration service at /services/database-administration/ available for ongoing stewardship.
Performance Optimization
Slow PostgreSQL is almost always diagnosable. We work from EXPLAIN ANALYZE, pg_stat_statements, autovacuum logs, and real production metrics rather than guesswork. Common levers include index design, query rewrites, partitioning of high-volume tables, autovacuum tuning on high-churn tables, bloat remediation, and connection-pooling adjustments. The deliverable is a prioritized plan with measured before and after numbers.
Legacy PostgreSQL Modernization
We offer incremental modernization for PostgreSQL environments stuck on unsupported releases such as 9.x, 10, 11, or 12, and for clusters approaching end of life on 13 or 14. Our upgrade path uses pg_upgrade where the maintenance window allows and logical replication where near-zero downtime or a cloud migration is in scope. We also modernize legacy self-managed clusters onto managed services such as Amazon RDS, Aurora PostgreSQL, Azure Database for PostgreSQL, or Google Cloud SQL. The database remains available throughout, no big-bang cutovers.
PostgreSQL Support & Maintenance
We provide ongoing support for production PostgreSQL, including minor-version patching, backup and point-in-time recovery validation that actually gets exercised, monitoring and alerting on the metrics that matter, failover drills, and steady attention to bloat, vacuum health, and index drift. Maintenance engagements are sized to the real footprint of your environment and keep your database healthy rather than letting issues compound.
Why PALADEM?
- Built for production PostgreSQL. Our PostgreSQL work targets long-lived, mission-critical databases where reliability, recoverability, and performance under real load matter more than a quick win.
- US-Based Architecture, Global Delivery. Senior US architects lead every engagement, supported by a global engineering team for efficient, cost-effective delivery. See our full services for how we structure engagements.
- Software Stewardship Approach. Every PostgreSQL engagement is guided by our Software Stewardship Framework™, which treats your database as a long-lived asset to be cared for across all eight stewardship pillars rather than a one-time deliverable.
Related PALADEM Services
Expertise translates into practice through PALADEM’s service lines. These are the most commonly engaged services alongside or instead of expertise-specific work.
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Learn moreFrequently Asked Questions
Our PostgreSQL is several major versions behind. What is the upgrade path?
There are two practical paths. pg_upgrade is fast and works well for in-place upgrades when the maintenance window allows a brief outage and the extension set is upgrade-clean. Logical replication is the right choice when downtime must be near zero, when you are also moving to a new host or managed service, or when you want to test the target under production traffic before cutover. We assess extension compatibility, replication slots, and application cutover mechanics up front so the plan matches your real constraints rather than a generic checklist.
We run PostgreSQL on-prem and want to move to a managed service. How do you approach that?
The shape of the migration depends on the destination. Amazon RDS, Aurora PostgreSQL, Azure Database for PostgreSQL, and Google Cloud SQL each have different extension support, replication options, and operational models. We start with a compatibility assessment of extensions, server parameters, authentication, and any custom background jobs, then design a staged cutover using logical replication or AWS DMS depending on the environment. The application remains shippable throughout, and we validate the target under real load before the final switch.
How do you approach PostgreSQL query performance tuning?
Performance work is evidence-based, not guesswork. We start with EXPLAIN ANALYZE on the actual problem queries, review pg_stat_statements to find the real hot spots, and inspect indexing, statistics, autovacuum behavior, and connection pooling. From there we prioritize fixes by impact: better or fewer indexes, query rewrites, partitioning where it pays off, autovacuum tuning on high-churn tables, and PgBouncer configuration. The deliverable is a written plan with before and after measurements so the improvement is verifiable rather than anecdotal.
How do you design high availability, replication, and failover for PostgreSQL?
High availability is a design decision tied to your real recovery objectives, not a product choice. For self-managed clusters we typically use streaming replication with Patroni or pg_auto_failover for orchestrated failover, backed by WAL archiving and tested point-in-time recovery. On managed services we use the provider primitives such as RDS Multi-AZ or Aurora replicas. In every case we insist on failover runbooks that have actually been executed, and on backup restores that have actually been validated, because untested recovery is not recovery.
Can we add vector search to our existing PostgreSQL for AI and RAG workloads?
Usually yes. pgvector has matured into a production-grade extension and is supported on the major managed services, which lets you keep your operational data, relational integrity, and vector embeddings in a single database. We assess whether your workload fits pgvector or genuinely needs a dedicated vector store, design the embedding and indexing strategy, and integrate retrieval into the application. This work often becomes the database layer behind PALADEM’s agentic AI engagements without forcing a second datastore into the architecture.