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Supabase is a well-known open-source Firebase alternative. It’s a managed Postgres + GoTrue + PostgREST + Realtime + Storage stack with web/mobile SDKs. Pylon hits the same problem space with a different shape.

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TL;DR

  • Choose Supabase if you want full Postgres SQL surface, you’re comfortable with multi-service deployments, or you need pgvector + edge functions + storage in one place.
  • Choose Pylon if you want one binary on a VPS, native faceted search, or a tighter integration between sync and policies.

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Architecture

Supabase is a curated stack of best-in-class single-purpose services. Pylon is one binary that does many of those things itself. Both are valid; pick the trade-off.

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Same shape

Both ship:
  • Real-time subscriptions over WebSocket
  • Built-in auth (magic links, password, OAuth)
  • File storage
  • Row-level access control (RLS for Supabase, policies for Pylon)
  • Web SDK + mobile SDKs
  • Self-hostable, FOSS-licensed
  • Managed cloud option

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Where Supabase is better

  • Full Postgres — every Postgres feature works: CTEs, window functions, JSONB operators, materialized views, foreign data wrappers, GIST indexes, partitioning. Pylon’s query layer is intentionally limited.
  • pgvector — first-class vector search via Postgres extension. Pylon has the vector_search plugin (in-memory), but for million-scale vectors Supabase wins.
  • PostgREST auto-API — every table becomes a REST endpoint automatically. Pylon also auto-generates these (/api/entities/<name>) but PostgREST has 8 years of battle-testing.
  • Edge Functions — globally distributed Deno runtime; nice for latency-sensitive endpoints. Pylon functions run in your single binary’s region.
  • Larger ecosystem — more libraries, more tutorials, more StackOverflow answers, more job postings.
  • Database UI — Supabase Studio is excellent for SQL exploration. Pylon Studio is more focused on entity inspection.

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Where Pylon is better

  • One service — one binary plus Bun, one port, one config file. Compare to a Docker Compose stack.
  • Faceted search — Supabase has Postgres tsvector for FTS but no native facets (docs). Pylon ships FTS5 + roaring-bitmap facet counts.
  • Game shards — Shard<S: SimState> for tick-based multiplayer (authored in Rust, with a useShard client hook; there’s no TypeScript shard-authoring API yet). Supabase has nothing equivalent.
  • In-process mutations — Pylon mutations run as typed handler-level transactions in the app process. Supabase Edge Functions are separate Deno functions that call Postgres over HTTP or a database client, so you manage transaction boundaries explicitly.
  • CRDTs — Pylon integrates Loro for collaborative editing. Supabase Realtime gives you Postgres Changes, Broadcast, and Presence; CRDT-backed collaborative data is still something you bring yourself.
  • Plugin system — built-in plugins for cross-cutting concerns such as search, files, presence, audit logs, and payments. Supabase has extensions, but they’re Postgres extensions, not framework-level.
  • TypeScript declarative schema — entity("User", {...}) in TS. Supabase uses SQL migrations; you can codegen TS types from them but the source of truth is SQL.

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Functions

Pylon’s “mutation = transaction” model is a meaningful difference. Throw inside a mutation and everything rolls back. Supabase Edge Functions can do this with explicit transaction handling, but it’s not the default shape.

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Pricing

Supabase’s free tier is generous for prototypes and includes managed Postgres. Pylon Cloud includes the application runtime, sync, domains, deploys, and machine hosting; self-hosted Pylon puts those costs on your own infrastructure.

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Migrating from Supabase

If you’re moving an existing Supabase app: The biggest delta today: Pylon’s entity API is the data API. If your app relies on raw Postgres queries (CTEs, window functions, materialized views, pgvector), you have two options:
  1. Express the logic in a Pylon action in TypeScript — for joins and aggregates this is usually fine, and you keep the type-safe entity model.
  2. Run a sidecar against the same Postgres — Pylon doesn’t lock the DB; you can connect any tool that speaks Postgres for analytics, BI, or specialized queries.
Raw SQL exposure from inside action handlers (e.g. ctx.pg.query(sql, params) in postgres-live builds) is on the roadmap; there’s no architectural reason to gate-keep it. For now, most app workloads fit the entity API; if yours needs more Postgres surface, Supabase has a head start.

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Honest weakness

Supabase’s Postgres-native data layer is more flexible than Pylon’s for analytics, complex queries, and integrations with tools that speak SQL (Metabase, Hex, Mode, Retool). If your data model needs to interop with a wider data ecosystem, Supabase’s “it’s just Postgres” is genuinely valuable.

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Both / and

Pylon supports Postgres as a backing store via the postgres-live feature. You can run Pylon as the application layer (entities, policies, functions, sync) on top of an existing Supabase Postgres instance. Some teams do this to keep Supabase Studio’s SQL UI for exploration while getting Pylon’s sync engine and facets for the app.