Alright, let's start by setting up some constraints in our database schema. This helps us avoid problems like duplicate entries or breaking business rules. We can use unique constraints, foreign keys, and check constraints to keep our data clean and tidy, even when multiple people are writing to the database at the same time.

CREATE TABLE users (
    id serial PRIMARY KEY,
    email VARCHAR ( 50 ) UNIQUE NOT NULL
);

Next up, let's talk about Row-Level Security (RLS). This is a nifty way to control who can do what with specific rows in your tables. By setting up these policies, you can manage who gets to see or change data, which is super useful for handling concurrent access.

ALTER TABLE your_table
    ENABLE ROW LEVEL SECURITY;

CREATE POLICY "select_billing_policy" 
    ON billing 
    USING (user_id = auth.uid());

Now, let's dive into optimistic locking. This involves adding a version column to your tables. Every time you update a row, this column increments. This way, your application can spot conflicts and handle them gracefully.

Add the version column:

ALTER TABLE your_table
    ADD COLUMN version integer DEFAULT 1;

Update your application logic to check and increment the version:

UPDATE your_table 
SET column1 = value1, version = version + 1 
WHERE id = :id AND version = :currentVersion;

Supabase Realtime is a game-changer. It can notify your clients about database changes in real-time. Integrate it with your client-side code to keep everything in sync and handle concurrent changes smoothly.

First, install the @supabase/realtime-js library:

npm install @supabase/realtime-js

Then, subscribe to table events:

import { RealtimeClient } from '@supabase/realtime-js'

const REALTIME_URL = 'wss://your-supabase-url.realtime.supabase.co/realtime/v1'
const realtime = new RealtimeClient(REALTIME_URL, {
  params: { apikey: 'public-anon-key' }
})

realtime.connect()

realtime.channel('public:your_table')
  .on('INSERT', payload => { console.log('New record!', payload) })
  .subscribe()

Database transactions are your best friend when it comes to making sure all your writes are atomic. By grouping multiple operations into a single transaction, you can avoid partial updates and keep your data consistent.

BEGIN;

UPDATE accounts
SET balance = balance - 100
WHERE id = 1;

UPDATE accounts
SET balance = balance + 100
WHERE id = 2;

COMMIT;

Database triggers are like little helpers that enforce business rules automatically when concurrent writes happen. They help keep everything consistent across your database operations.

CREATE OR REPLACE FUNCTION update_updated_at_column()
RETURNS TRIGGER AS $$
BEGIN
   NEW.updated_at = NOW();
   RETURN NEW;   
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER update_user_modtime
BEFORE UPDATE ON users
FOR EACH ROW
EXECUTE PROCEDURE update_updated_at_column();

Finally, let's set up some monitoring and alerts to catch any issues related to concurrent writes. Tools like Supabase Insights or other external monitoring services can be really handy for this.

Enable monitoring in Supabase:

supabase insights enable

Set up alerts for specific events:

supabase alerts create --condition 'errors > 10' --action 'notify'

And there you have it! With these steps, you'll be well on your way to handling concurrent writes like a pro. Happy coding!