Five managed databases evaluated across the three core multi-tenancy patterns — shared schema with RLS, schema-per-tenant, and database-per-tenant. Picks span distributed SQL, full-stack BaaS, MySQL-compatible HTAP, and single- and multi-cloud managed Postgres.
Before picking a database, you need to know which tenancy model you're committing to. There are three broad patterns, and they map directly to your isolation, scalability, and compliance requirements3:
tenant_id column. Row-Level Security (RLS) enforces isolation at the database layer. This is the simplest to operate and the recommended default3.AWS's prescriptive guidance frames these similarly as pool, bridged, and silo models, and emphasizes that RLS is the key mechanism for enforcing tenant data isolation within a single PostgreSQL table in the shared-schema approach2.
The decision matters because it constrains everything downstream: your migration strategy, your backup story, your per-tenant compute costs, and whether you can scale writes across regions.
We looked at five managed databases across six dimensions that matter for multi-tenant SaaS:
A distributed databases deep-dive frames the landscape well: strict consistency plus global writes points you toward Spanner, CockroachDB, Yugabyte, or Aurora DSQL; serverless and edge use cases point toward Neon, Supabase, or PlanetScale; and the full Postgres extension ecosystem lives in Supabase, Neon, and RDS6.
CockroachDB is a distributed SQL database that speaks the Postgres wire protocol, which means your existing Postgres drivers and ORMs work without modification6. What sets it apart for multi-tenant SaaS is REGIONAL BY ROW — a SQL-level directive (ALTER TABLE ... SET LOCALITY REGIONAL BY ROW) that lets you pin individual tenant rows to specific geographic regions6. That's a direct answer to data-residency requirements without standing up separate database instances per region.
The serverless tier offers scale-to-zero, so tenants with low activity cost nearly nothing. Strong consistency is guaranteed via Raft consensus and hybrid logical clocks (HLC)6, which matters when you can't tolerate split-brain writes across regions. PingCAP's comparison names CockroachDB as the best choice for Postgres-compatible distributed SQL1.
Verdict: If your SaaS needs strict consistency and multi-region writes, this is the clear top pick. The trade-off is that CockroachDB's Postgres compatibility, while strong, doesn't cover the full extension ecosystem you'd get from vanilla Postgres6.
Supabase is a backend-as-a-service platform built on vanilla Postgres5. The key differentiator for multi-tenant SaaS is that RLS is deeply integrated with Supabase Auth — your clients can hit PostgREST directly and the database enforces tenant isolation without an intermediary API layer5. That's a meaningful simplification for shared-schema tenancy.
Supabase also ships pgvector built-in, which is relevant if your SaaS has any AI or semantic-search features. Both Supabase and Neon achieve SOC 2 Type 2 and HIPAA compliance5, so you're not sacrificing enterprise readiness by choosing the BaaS route.
Verdict: The fastest path to a multi-tenant SaaS with shared-schema tenancy. Choose this if you want auth, storage, realtime, and edge functions bundled with your database. If you only need a standalone database without the platform layer, Neon is the better fit5.
TiDB is a MySQL-compatible distributed SQL database with HTAP built in — it maintains a row store for OLTP and a columnar store (TiFlash) for analytics within the same system6. For multi-tenant SaaS, that means you can run operational queries and tenant-level analytics without maintaining a separate OLAP pipeline.
PingCAP's own comparison positions TiDB as the best overall distributed SQL for multi-tenant SaaS at scale1, and it offers horizontal scaling that single-node MySQL can't match. A free tier makes it accessible for early-stage SaaS.
Verdict: The right pick if your team lives in the MySQL ecosystem and needs analytical queries on tenant data without a separate data warehouse. The trade-off is that you're outside the Postgres extension ecosystem entirely.
Cloud SQL is Google Cloud's managed PostgreSQL offering. It supports RLS natively (since it's vanilla Postgres under the hood), offers high availability configurations, managed backups, and predictable mid-band pricing. For teams already anchored in Google Cloud, it's the path of least resistance for shared-schema multi-tenancy.
The full Postgres extension ecosystem is available6, which matters if you depend on extensions like pg_partman for time-based partitioning or pg_cron for scheduled maintenance tasks.
Verdict: A reliable default for GCP-anchored SaaS that needs managed Postgres without distributed-SQL complexity. The limitation is that it's a single-region, single-cloud product — no multi-region write scaling out of the box.
Aiven lets you deploy managed PostgreSQL across AWS, GCP, and Azure from a single control plane. It's open-source based, which means you're running standard Postgres with full extension support and no proprietary lock-in at the database layer. For SaaS with data-residency requirements that span multiple cloud providers or regions, this flexibility is the core value proposition.
Verdict: The pick for teams that need to avoid cloud lock-in or have data-residency requirements across providers. You trade some of the platform integration you'd get from a first-party cloud database (like Cloud SQL's tight GCP coupling) for deployment flexibility.
Here's how to narrow it down:
REGIONAL BY ROW tenant pinning and Raft consensus give you what you need6.Some of the links on this page are affiliate links. If you click through and sign up, we may earn a commission. That doesn't influence our rankings — we pick based on what fits each use case, and we'll tell you when something isn't worth buying.
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