Technology
PostgreSQL Development & Consulting Services
Production PostgreSQL — schema design, query tuning, replication, partitioning, and the operational discipline a serious database deserves.
What we build with PostgreSQL
- Schema design, indexing strategy, and EXPLAIN-driven query tuning
- Replication topologies: streaming, logical, and Aurora replica fleets
- High-availability: Multi-AZ, Patroni, Stolon, or cloud-native HA
- Partitioning for billion-row tables and time-series workloads
- Vector search with pgvector for AI / RAG workloads at production scale
- Full-text search with tsvector + GIN indexes
- JSONB column patterns with proper indexing (GIN, partial, expression)
- TimescaleDB for time-series-heavy workloads
- PostGIS for geospatial workloads
- Connection pooling with PgBouncer, RDS Proxy, or pgcat
- Managed Postgres on RDS, Aurora, Cloud SQL, Azure Database, Crunchy Bridge, Neon, Supabase
- Self-managed Postgres on EC2, EKS (via CloudNativePG or Zalando operator), or on-prem
- Zero-downtime migrations from Oracle, MySQL, SQL Server, or older Postgres versions
- Backup verification, PITR drills, and cross-region DR strategies
- Performance monitoring with pg_stat_statements, auto_explain, and Datadog DBM
- Postgres extensions: pg_partman, pgcrypto, pg_audit, citus, hypopg, and others
- Logical replication for read-replicas, cross-region copies, and CDC pipelines
- Row-level security policies for multi-tenant SaaS
Why DiveScale
Built by engineers who ship PostgreSQL in production
Postgres is the most boringly excellent database choice for most workloads. DiveScale brings the operational discipline that makes it stay that way: indexes that match the query plan, partitioning before tables become unmanageable, and replication topologies that actually survive failover.
We work across managed (RDS, Aurora, Cloud SQL) and self-managed. The choice depends on cost, control, and the specific features your workload needs (Aurora I/O-optimized, RDS Multi-AZ Cluster, vanilla Postgres extensions).
And we keep pace with the modern usage. pgvector for embeddings and RAG. Logical replication for zero-downtime migrations. PostgreSQL 16+ features like incremental backups and parallel commit. The database catches up; we keep your deployment current.
PostgreSQL use cases we deliver
How we deliver
Our PostgreSQL delivery process
- 01
Audit the database
Schema review, slow-query analysis, index usage, replication lag, and vacuum behavior baseline.
- 02
Targeted fixes
Index changes, query rewrites, partitioning, and connection pooling — the highest-impact wins first.
- 03
Topology & DR
Replication design, backup verification, failover testing, and disaster recovery runbooks.
- 04
Operate or hand off
Ongoing DBA-as-a-service or hand-off with monitoring, alerting, and on-call playbooks.
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Aurora for AWS-heavy shops needing read scale and fast failover. RDS for vanilla Postgres with managed ops. Cloud SQL on GCP. Self-managed only when extensions or HA needs go beyond managed offerings.
