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Announcing Springtail for Supabase

Photo of George Szundi, co-founder of Springtail.
George Szundi
GTM
3 minute read October 13, 2025

We're excited to announce that Springtail is an official Supabase integration, bringing elastic read scaling to the popular open-source Postgres development platform.

If you're handling variable traffic patterns or read-heavy workloads, this integration gives you flexible read capacity that scales with demand.

As your product grows, read volume can start to outpace what a single primary database can handle. Analytics queries slow down, features lag, and you face difficult trade-offs: wasteful always-on replicas, expensive vertical scaling, or even a dreaded re-architecture project.

This is where Springtail can help.

Elastic read scaling for Supabase

Springtail adds read capacity to Supabase that scales with your workload. Quickly spin up replicas when demand increases and scale down when demand drops — all without code changes or additional infrastructure to manage.

With Springtail, Supabase users can:

  • Improve performance for read intensive workloads
  • Handle variable traffic without over-provisioning
  • Reduce cost by scaling replicas only when needed

How it works

Springtail connects to your Supabase Postgres database using logical replication. It maintains a real-time copy of your data and manages replica lifecycle, scaling, and load balancing behind a single endpoint.

Your application simply connects to Springtail's Postgres-compatible coordinator, which automatically:

  • Routes read queries to Springtail replicas
  • Sends write queries to your Supabase primary
  • Handles connection pooling and failover
Springtail read scaling for Supabase using logical replication, shared storage layer, and elastic compute nodes.

From your application's perspective, nothing changes. Springtail is completely transparent, giving you highly scalable read capacity with near-zero dev effort.

Fast replica provisioning

Traditional read replicas must copy the entire dataset before serving queries, which makes them slow to start. Springtail uses a shared storage layer across replicas, allowing each new replica to access data immediately.

This means replicas can start in seconds, giving you extra capacity when you need it, and letting you scale down just as easily when demand drops.

The result? Elastic read scaling that matches demand so you only pay for replicas when you need them. No more over-provisioning or added complexity.

Common use cases

Supabase developers use Springtail for all kinds of read-intensive workloads.

Resource contention

Run complex analytical queries or nightly batch jobs on dedicated replicas without impacting production workloads.

Handle traffic spikes

Scale read capacity during launches, viral moments, or seasonal peaks, then scale back down to save costs.

Serve read-heavy datasets

Efficiently serve dashboards, product catalogs, or user profiles that see high read volume with minimal writes.

Get started

Setup takes as little as 15 minutes.

Explore our docs or talk to us to get started. We’d love to hear what you’re building and help you keep scaling with Supabase.