No-code apps and databases decision

PlanetScale

A competent engineer can build a minimal self-hosted Postgres service that covers small dev/prod needs, but reproducing PlanetScale’s NVMe Metal performance, sharding (Vitess/Neki), SLA, and enterprise-grade compliance/support is impractical without significant infra and operational investment.

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You pay

$5/mo

$60/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$20/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 5 seats.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Provide a single-node hosted PostgreSQL instance with connection pooling, automated backups, basic metrics, and a simple workflow for isolated development environments (branch-per-environment).

What it still won’t have

  • Vitess-style horizontal sharding and automated resharding workflows
  • PlanetScale Metal NVMe performance and unlimited IOPS
  • 99.99%+ SLA and multi-region managed HA with automated failover
  • Branching implemented as first-class, millisecond-prorated branch clusters
  • Enterprise support, compliance attestations (SOC2, PCI DSS, HIPAA BAA) and managed migration assistance

What remains hard

  • Infrastructure at scaleOur blazing fast NVMe drives unlock unlimited IOPS , bringing data center performance to the cloud.
  • Brand trustPlanetScale is trusted by some of the world’s largest brands.
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 5 seats.

Paid seatsseats

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

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What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a self-hosted single-node PostgreSQL service on AWS using Ubuntu 22.04, systemd, and Docker Compose. In scope: (1) provision an EC2 t4g.small (or equivalent) with an attached EBS volume and bootstrap PostgreSQL 15; (2) deploy PgBouncer for connection pooling and expose a single connection endpoint; (3) implement automated backups to S3 using WAL shipping and daily logical backups, plus a restore script; (4) provide a simple API (Node.js/Express) and small web UI to create/delete per-branch databases (or schemas), return connection strings, and show backup status; (5) export Postgres metrics to Prometheus and ship a Grafana dashboard; (6) include health checks, logging, and basic access controls. Out of scope: horizontal sharding (Vitess-style), multi-region/global edge routing, NVMe-level performance tuning, enterprise support, and compliance certifications. Require automated tests for backup/restore and branch creation, error handling for failures (disk, backup, restore), and deploy scripts (Terraform for infra and systemd/Docker Compose for services).
How we checked3 sources · 3/3 runs agreed · evidence score 59

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-3
  • Evidence score59

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 2 moats quoted from the page