Every few months a new database promises 10x performance, infinite scale, and a developer experience that finally Just Works. Most teams should ignore them.
Postgres, in 2026, is still the right default for >90% of products.
A concrete example
Here's a typical RLS policy we ship on day one of a multi-tenant SaaS:
-- Enable RLS and scope every read/write to the caller's tenant.
alter table public.invoices enable row level security;
create policy "tenant_isolation"
on public.invoices
for all
to authenticated
using (tenant_id = auth.jwt() ->> 'tenant_id')
with check (tenant_id = auth.jwt() ->> 'tenant_id');
That's three lines of SQL and you've eliminated an entire class of "wrong tenant saw wrong data" bugs.
Why Postgres still wins
- Maturity: 25+ years of production hardening
- Flexibility: relational, JSON, full-text search, vector — all in one engine
- Tooling: the entire ORM and analytics ecosystem speaks Postgres
- Hiring: every senior engineer already knows it
Why Supabase on top of it
Supabase doesn't replace Postgres — it gives you the operational layer that startups skip and pay for later:
- Row-Level Security as a first-class concern (use it from day one)
- Realtime without standing up your own message bus
- Auth that integrates cleanly with RLS policies
- Storage for files alongside your relational data
You get a managed Postgres without locking yourself out of dropping down to raw SQL when you need to.
When we don't reach for it
- OLAP workloads at >100M rows — use ClickHouse or BigQuery
- Sub-millisecond key-value at extreme QPS — use Redis or DynamoDB
- Search-as-a-product — Algolia or a dedicated Elasticsearch cluster
Mix and match. Postgres for the system of record, specialized engines for specialized workloads.
Need help architecting your Postgres + Supabase setup? Get in touch.