What this is, and who it is for
This practice covers the parts of PostgreSQL that decide whether a product can grow: connection pooling with PgBouncer or Supavisor, continuous WAL archiving to object storage with WAL-G for point-in-time recovery, zero-downtime DDL on very large tables, and vector search with pgvector and HNSW indexes as a self-hosted alternative to managed vector databases. It is for teams whose database is the bottleneck under concurrency, whose recovery plan has never been tested, or who are paying managed vector database prices for workloads PostgreSQL already handles.
Start a conversationTune high-concurrency relational workloads with PgBouncer connection pooling, automated point-in-time recovery (WAL-G), and zero-downtime migrations.
Based in Casablanca (GMT+1): overlapping working hours with European teams and a morning overlap with North America.
Database Architecture & PostgreSQL
Capabilities
PgBouncer & Supavisor pooling config
Automated WAL-G backup & PITR restore
High-speed vector indexing (pgvector)
Query optimization & zero-downtime DDL
Delivered architecture
Zero-Downtime PostgreSQL Disaster Recovery
Questions, answered
Technical questions, answered directly.
What is the recovery point objective for this architecture?
Strictly sub-minute. Continuous Write-Ahead Log streaming via WAL-G to S3 object storage gives a sub-minute RPO with automated point-in-time recovery, so a restore lands on a chosen second rather than the last nightly snapshot.
How long does a restore actually take?
A verified recovery of more than 100GB completed in under 12 minutes with zero data corruption.
Why is connection pooling part of the design?
PostgreSQL allocates a backend process per connection, so high concurrency exhausts memory and latency long before CPU. PgBouncer or Supavisor pools and multiplexes client connections so the database sees a stable, small number of backends.
Can schema migrations run without downtime?
Yes. Adding indexes and constraints on tables with hundreds of millions of rows is done with concurrent DDL and staged backfills, so the application never takes an outage for a schema change.
Can PostgreSQL replace a dedicated vector database?
For most workloads, yes. pgvector with HNSW indexes scales to millions of embeddings, which removes a separate managed service, its cost and its data-egress boundary.
Database Architecture & PostgreSQL