The Quest for a Plug‑and‑Play Sync Layer

A recent Hacker News thread (source: https://news.ycombinator.com/item?id=46374814) captured a common pain point for modern web developers: how to give an application the feel of a native app—instant updates, optimistic UI, and offline resilience—while still using a traditional relational database such as Postgres on AWS RDS. The poster lists a handful of contenders—Convex, ElectricSQL, Zero, Liveblocks—yet laments that each feels “modular” and falls short in key areas.

The underlying problem is deceptively simple: take a Postgres database, expose it to a browser or mobile client, and keep the client state in sync with the server with minimal latency and maximum developer ergonomics.

What a Real‑Time Sync Engine Must Deliver

1. Native Postgres backend – the engine should piggyback on an existing RDS instance, leveraging its ACID guarantees.
2. Backend‑centric query execution – developers want to write queries in the same language as their business logic (Python/SQLAlchemy, Node/Drizzle, etc.) and have the sync layer translate them to client‑friendly subscriptions.
3. Schema‑first declaration – reuse existing ORM or schema definitions so that the sync layer stays in sync with the database schema.
4. Developer‑friendly SDK – a thin wrapper that lets a React or Svelte component subscribe to a query and receive incremental updates.
5. Scalability knobs – support for connection pooling, sharding, read replicas, and eventual consistency across data centers.

Why Most Off‑the‑Shelf Solutions Fall Short

In short, these tools either replace Postgres with a custom data store, or add a layer that requires its own deployment and management. Neither satisfies the desire for a single, cohesive stack that uses the same database, ORM, and query language.

The Architecture of a “Postgres‑First” Sync Engine

A viable approach is to build a thin sync service that sits between the database and the clients, using Postgres’s own change‑data‑capture (CDC) mechanisms. The core components are:

1. Logical Replication Slot – Postgres streams every DML operation as a logical change.
2. Change Processor – A lightweight worker (e.g., a FastAPI endpoint or a background task) that reads the replication stream, applies conflict‑resolution rules, and pushes updates to clients via WebSockets or Server‑Sent Events.
3. Subscription API – Clients subscribe to a query by sending a SQL‑like statement; the server validates the query, sets up a subscription ID, and streams rows that match the predicate.
4. Schema Registry – A JSON or Protobuf schema that mirrors the ORM definitions, ensuring that the client knows the shape of the data.
5. Auth & Permissions – A middleware layer that intercepts subscription requests and enforces row‑level security.

Sample Flow

# FastAPI endpoint for subscription
@app.post("/subscribe")
async def subscribe(req: SubscribeRequest, user=Depends(auth)):
    # Validate the SQL query against the user's permissions
    stmt = validate_sql(req.query, user)
    # Register the subscription and return an ID
    sub_id = await subscription_manager.register(stmt, user)
    return {"subscription_id": sub_id}

On the client side:

// React hook that subscribes to a query
const useRealtimeQuery = (query) => {
  const [rows, setRows] = useState([]);
  useEffect(() => {
    const ws = new WebSocket("wss://api.example.com/subscribe");
    ws.onopen = () => ws.send(JSON.stringify({ query }));
    ws.onmessage = (e) => setRows(JSON.parse(e.data).rows);
    return () => ws.close();
  }, [query]);
  return rows;
};

This pattern keeps the database untouched, reuses existing ORM schemas, and gives the client an API that feels like a normal query but is backed by real‑time updates.

Scaling Challenges

Existing Tools Worth a Second Look

• Postgres Logical Replication + WebSockets – A DIY approach that gives full control; many open‑source projects (e.g., pgoutput + socket.io) illustrate the pattern.
• Supabase Realtime – Built on top of Postgres’s replication, it offers a subscription API but requires a Supabase instance.
• Hasura – GraphQL‑first, but its real‑time engine is essentially the same pattern; it can be used with a custom backend if you prefer SQL over GraphQL.
• ElectricSQL – While it adds a sync layer, its open‑source core can be forked and adapted to a Postgres‑first workflow.

Bottom Line

A truly “Postgres‑first” real‑time sync engine is not a silver bullet, but it is achievable with a modest architectural investment. By leveraging logical replication, a lightweight subscription API, and careful attention to scaling, developers can give their web apps the feeling of a native experience without abandoning the comforts of a relational database. The key is to keep the sync layer thin and composable with existing tools, rather than replacing the database or the ORM.

“The biggest barrier isn’t the technology; it’s the mindset that a sync engine must be a separate monolith.” – Anonymous contributor on Hacker News.