Pylon vs. Supabase
Supabase packages Postgres with GoTrue, PostgREST, Realtime, Storage, and Studio. Pylon provides most of that surface in one binary and can run on Postgres. The choice comes down to the trade-offs below.
You want raw SQL as your primary interface (CTEs, materialized views, pgvector), you're comfortable operating multi-service deployments, or you need Postgres tools (Metabase, Hex, Retool) hitting your data directly.
You want one binary on a VPS, native faceted search with live counts, in-process functions that share a transaction with your writes, or a typed entity API + realtime sync over the same data.
Architecture at a glance
| Pylon | Supabase | |
|---|---|---|
| Process count | 1 | 7+ (Postgres, GoTrue, PostgREST, Realtime, Storage, Studio, Edge Functions) |
| Default DB | SQLite (Postgres optional) | Postgres (required) |
| Backed by | Rust | Postgres + Go + Elixir + Deno |
| Self-host | scp + systemctl | docker-compose with 7+ containers |
| Schema source of truth | TypeScript (entity()) | SQL migrations |
| Faceted search | Native (full-text + facets) | tsvector for FTS, build facets yourself |
| Function-to-DB latency | <1ms (same process) | 50–200ms (Edge → Postgres) |
What both ship
- Real-time subscriptions over WebSocket
- Built-in auth with magic links, password, and OAuth
- File storage with signed URLs
- Row-level access control (RLS for Supabase, policies for Pylon)
- Web + mobile SDKs
- Self-hostable, FOSS-licensed
- Managed cloud option
Where Supabase wins
Every Postgres feature is one query away: CTEs, window functions, JSONB operators, materialized views, foreign data wrappers, and partitioning. Pylon can run on Postgres, but exposes a typed entity API rather than arbitrary SQL.
pgvector's approximate indexes (HNSW, IVFFlat) handle million-row vector tables. Pylon ships built-in vector search (field.vector + ctx.db.vectorSearch) as exact k-NN — perfect recall and zero index maintenance to roughly 100k rows per entity; past that, pgvector's ANN wins.
More libraries, more tutorials, more StackOverflow answers, more job postings. Years of battle-testing on PostgREST. Mature integrations with Metabase, Hex, Retool.
Supabase Studio is excellent for ad-hoc SQL. Pylon Studio focuses on entity inspection.
Where Pylon wins
Pylon uses one service, one port, and one config file. A comparable Supabase deployment uses docker-compose with Postgres, GoTrue, PostgREST, Realtime, Storage, Studio, and Edge Functions.
Add search: to an entity and get full-text hits and live facet counts in one call. Supabase has tsvector for full-text search; facets require custom queries.
embedding: field.vector(1536) is one schema line; ctx.llm.embed and ctx.db.vectorSearch are built in. No extension to enable, no index DDL, no separate vector database until you genuinely outgrow exact search.
A Pylon mutation runs in-process with ctx.db and rolls back when it throws. Supabase Edge Functions are separate processes that reach Postgres over HTTP, so atomicity needs an explicit BEGIN/COMMIT.
Supabase Realtime streams raw row changes (Postgres Changes) and leaves optimistic-write reconciliation to your client. Pylon's sync engine pushes server-computed diffs and reconciles your optimistic writes for you.
Server-render your frontend from the process that holds your data. Supabase pairs with a separate Next.js host and an API hop between origins.
Moving from Supabase
| Supabase | Pylon |
|---|---|
| SQL schema + RLS | entity() + policy() in TypeScript |
| supabase.from('todos').select() | db.useQuery("Todo") |
| supabase.auth.signInWithOtp(...) | magic-link auth, built in |
| Storage buckets | presigned uploads (S3 / R2 / local) |
| Edge Functions | mutation / action in functions/*.ts |
| Realtime subscriptions | db.useQuery (server-authoritative) |
| auth.users | Pylon's User entity (you control the shape) |
Supabase exposes raw SQL as the primary interface, with direct SQL-tool interop (Metabase, Hex, Mode, Retool) and the full Postgres feature set one query away. Pylon can use the same Postgres, but reaches data through a typed entity API. Supabase is a better fit today for ad-hoc analytics and the wider SQL ecosystem.
Try Pylon for yourself.
Scaffold a full-stack app in seconds and deploy free on Cloud.