Supabase is a backend platform built around PostgreSQL. It provides a database, file storage, authentication, APIs, realtime capabilities, serverless functions, and developer tools in one platform.

In this guide, we’ll explore its core features and how they fit into a Next.js application.

Architecture Overview

Next.js
                            │
                            ▼
                     Supabase Client
                            │
             ┌──────────────┼──────────────┐
             ▼              ▼              ▼
        PostgreSQL        Storage          Auth
             │
             ├── Tables and Relations
             ├── Row Level Security (RLS)
             ├── Triggers
             └── pgvector
             │
             ├──────────→ Realtime
             │
             └──────────→ Database Webhooks
                                  │
                                  ▼
                            Edge Functions
                                  │
                                  ▼
                            External APIs

1. PostgreSQL Database

PostgreSQL is the main database for storing structured application data, such as posts, users, products, orders, and categories.

Create a posts table:

create table posts (
  id uuid primary key default gen_random_uuid(),
  slug text unique not null,
  title text not null,
  content text,
  created_at timestamptz default now()
);

Read data from Next.js:

const { data, error } = await supabase
  .from("posts")
  .select("*");

The basic flow is:

Next.js → Supabase Client → PostgreSQL → posts

2. Storage

Supabase Storage stores files such as images, videos, PDFs, and documents. PostgreSQL typically stores the file path or metadata, while Storage holds the actual file.

Create a bucket named blog-media, then upload a file:

const { data, error } = await supabase.storage
  .from("blog-media")
  .upload("posts/monstera.webp", file);

Generate a public URL:

const { data } = await supabase.storage
  .from("blog-media")
  .getPublicUrl("posts/monstera.webp");

A typical structure looks like this:

PostgreSQL
└── cover_image = "posts/monstera.webp"

Storage
└── blog-media/posts/monstera.webp

Use private buckets and signed URLs when files should not be publicly accessible.

3. Authentication

Supabase Auth manages user authentication and supports email/password, magic links, one-time passwords (OTP), and OAuth providers.

Sign up:

const { data, error } = await supabase.auth.signUp({
  email,
  password,
});

Sign in:

const { data, error } =
  await supabase.auth.signInWithPassword({
    email,
    password,
  });

Get the current user:

const { data, error } = await supabase.auth.getUser();
const user = data.user;

The basic flow is:

User → Supabase Auth → Authenticated User → Protected Data

In Next.js, authentication should be integrated with an appropriate server-side session strategy when protecting server-rendered pages or backend operations.

4. Row Level Security (RLS)

Row Level Security controls which users can read, insert, update, or delete specific database rows.

Enable RLS on the posts table:

alter table posts enable row level security;

For example, users can be allowed to update only their own posts:

create policy "Users can update own posts"
on posts
for update
using (auth.uid() = user_id)
with check (auth.uid() = user_id);

This example assumes the table has a user_id column identifying each post’s owner.

The flow is:

User → Supabase → RLS Check → Database
                       ├── Allowed
                       └── Rejected

RLS is particularly important when the frontend accesses Supabase directly. Policies should be designed for every operation the application permits, rather than relying only on frontend checks.

5. Auto-Generated REST API

Supabase automatically provides a data API for PostgreSQL tables, allowing you to perform common CRUD operations without manually creating an endpoint for each table.

Read:

const { data, error } = await supabase
  .from("posts")
  .select("*");

Insert:

const { data, error } = await supabase
  .from("posts")
  .insert({
    title: "My Post",
    slug: "my-post",
  });

Update:

const { data, error } = await supabase
  .from("posts")
  .update({
    title: "Updated Post",
  })
  .eq("id", postId);

The basic flow is:

Next.js → Supabase API → PostgreSQL

For complex business logic, you may still need Next.js Route Handlers, Server Actions, or Supabase Edge Functions.

6. Realtime

Supabase Realtime allows the frontend to receive database changes without repeatedly polling the database.

For example, an order status can update automatically when the database changes.

supabase
  .channel("orders")
  .on(
    "postgres_changes",
    {
      event: "*",
      schema: "public",
      table: "orders",
    },
    (payload) => {
      console.log(payload);
    }
  )
  .subscribe();

Typical use cases include:

• Chat applications
• Notifications
• Live dashboards
• Order status updates

The basic flow is:

PostgreSQL → Realtime → Frontend

Make sure the relevant tables and permissions are configured for the changes your application needs to receive.

7. Edge Functions

Supabase Edge Functions are server-side functions useful for logic that should not run in the browser.

Common use cases include:

• Calling third-party APIs
• Using secret API keys
• Payment processing
• Handling webhooks
• Integrating AI APIs
• Sending emails

Create a function:

supabase functions new hello

Example implementation:

Deno.serve(async (req) => {
  return new Response(
    JSON.stringify({
      message: "Hello!",
    }),
    {
      headers: {
        "Content-Type": "application/json",
      },
    }
  );
});

Deploy it:

supabase functions deploy hello

Call it from Next.js:

const { data, error } =
  await supabase.functions.invoke("hello", {
    body: {
      name: "Viet",
    },
  });

The flow is:

Next.js → Edge Function → External API → Response

Keep secret keys on the server side and apply appropriate authentication and authorization to functions that perform sensitive operations.

8. Database Webhooks

Database Webhooks send HTTP requests when configured database events occur.

For example, when an order is created:

orders INSERT
     ↓
Database Webhook
     ↓
Edge Function
     ↓
Send Notification

You can configure a webhook through the Supabase Dashboard:

Supabase Dashboard
→ Database
→ Webhooks
→ Create Webhook

Select the table and event, such as:

Table: orders
Event: INSERT

Then specify the target endpoint, for example:

https://project.supabase.co/functions/v1/order-created

The key difference is:

Realtime → Database → Frontend
Webhook  → Database → HTTP Endpoint

Realtime is useful for delivering updates to connected clients. Webhooks are useful for triggering backend workflows in response to database events.

9. Database Triggers

A PostgreSQL trigger automatically executes database logic when a configured event occurs.

For example, you can create a profile record whenever a user signs up. Supabase Auth stores users in auth.users, while application profile data can live in public.profiles.

First, define the function:

create function public.create_profile()
returns trigger
language plpgsql
security definer
set search_path = ''
as $$
begin
  insert into public.profiles (id)
  values (new.id);

  return new;
end;
$$;

Then create the trigger:

create trigger on_auth_user_created
after insert on auth.users
for each row
execute function public.create_profile();

The flow is:

INSERT auth.users
       ↓
     Trigger
       ↓
PostgreSQL Function
       ↓
INSERT profiles

Use triggers for database-level automation such as maintaining timestamps, creating related records, or recording audit information.

Because this function uses security definer, its permissions and execution context should be reviewed carefully. Keep its privileges minimal and ensure the target table has appropriate access controls.

10. pgvector and Vector Search

The pgvector extension allows PostgreSQL to store and search vector embeddings. This makes Supabase useful for AI applications that require semantic search or Retrieval-Augmented Generation (RAG).

Enable the extension:

create extension if not exists vector;

Create a table:

create table documents (
  id uuid primary key,
  content text,
  embedding vector(1536)
);

The dimension 1536 must match the embedding model you use.

A typical RAG pipeline looks like this:

Document
   ↓
Embedding Model
   ↓
Vector
   ↓
PostgreSQL + pgvector
   ↓
Similarity Search
   ↓
Relevant Documents
   ↓
LLM
   ↓
Answer

A similarity search can look like this:

select
  id,
  content,
  1 - (embedding <=> query_embedding) as similarity
from documents
order by embedding <=> query_embedding
limit 5;

Here, query_embedding represents a vector supplied by the application. In a real query, it must be passed or defined using a compatible vector type.

This approach is useful for RAG applications, AI chatbots, semantic search, and knowledge bases.

11. Database Migrations

Database migrations store schema changes as version-controlled files. This makes changes reproducible across development, staging, and production environments.

Create a migration:

supabase migration new add_slug

Add the SQL:

alter table posts
add column slug text;

Apply local migrations to the remote database:

supabase db push

The typical workflow is:

Migration → Git → Deployment → Production Database

Migrations are especially useful when working in teams because database changes can be reviewed, tracked, and applied consistently.

12. Generated TypeScript Types

Supabase can generate TypeScript types from your PostgreSQL schema, helping keep database queries aligned with your application code.

Generate types:

supabase gen types typescript \
  --project-id YOUR_PROJECT_ID \
  > database.types.ts

A database table might look like this:

posts
├── id
├── title
└── status

The generated types describe its columns and their corresponding database types. For example, a simplified representation might be:

type Post = {
  id: string;
  title: string;
  status: string;
};

Use the generated Database type with the Supabase client:

import { createClient } from "@supabase/supabase-js";
import type { Database } from "./database.types";

const supabase = createClient<Database>(
  SUPABASE_URL,
  SUPABASE_KEY
);

The flow is:

PostgreSQL Schema
       ↓
Supabase CLI
       ↓
database.types.ts
       ↓
Next.js + TypeScript

The generated types provide better autocomplete and compile-time checks. They do not replace runtime validation of untrusted input.

13. Supabase CLI

The Supabase CLI is a command-line tool for developing and managing Supabase projects.

Common tasks include:

Supabase CLI
├── Local Development
├── Database Migrations
├── Generate TypeScript Types
├── Deploy Edge Functions
└── Database Management

Common commands:

supabase start
supabase migration new add_posts
supabase db push
supabase gen types typescript
supabase functions deploy hello

The CLI is especially useful when database schemas, Edge Functions, and other backend changes need to be managed through Git.

14. Logs and Monitoring

Supabase Logs help you investigate errors and understand what is happening inside your project.

Logs can help troubleshoot:

• API errors
• Database errors
• Authentication errors
• Storage errors
• Edge Function errors

You can access them through:

Supabase Dashboard
→ Logs

Monitoring focuses on the overall health and usage of the system, including:

Database Usage
API Requests
Error Rate
Performance
Storage Usage

A simple debugging workflow is:

Problem
   ↓
Supabase Logs
   ↓
Find Request or Error
   ↓
Identify Cause
   ↓
Fix

Combining logs with application-level monitoring makes it easier to identify and investigate production issues.

Conclusion

Supabase provides a broad set of backend capabilities around PostgreSQL, from database operations and authentication to file storage, realtime updates, serverless functions, and vector search.

For a Next.js application, these features can reduce the amount of backend infrastructure you need to build and maintain yourself.

Start with the database, authentication, and RLS. Then introduce Storage, Realtime, Edge Functions, or pgvector as your application’s requirements grow.

The key is to choose the features that solve your current problems while maintaining clear boundaries, secure access controls, and a reproducible development workflow.