A Supa Explanation of Supabase: The BaaS Everyone Is Talking About (And Why)

What is Supabase?

There are many products in this space, if you’ve used Firebase or Appwrite, you already know the category: BaaS (Backend as a Service).

When you build your first few projects, you eventually start seeing a pattern: the same backend pieces keep repeating like auth, database, storage, user management, file handling, etc. Every app needs them, and rebuilding those from scratch each time is exhausting.

That’s why tools like Firebase, Appwrite, and Supabase exist. They package these common backend building blocks into ready-to-use APIs, so you can focus on your frontend instead of spinning up servers, databases, and auth systems manually.

This means you can build an entire application in React or Next.js and directly interact with the BaaS no custom backend server needed for most use-cases.

So Supabase is one of these BaaS platforms, but it stands out because it’s built on top of PostgreSQL, is open-source, and gives you an SQL-first developer experience. And it handles scale enormously well.

In 2024, Supabase raised $100M in Series E funding, reaching a valuation of around $5B. Thas’s massive. But what made this possible? Supabase embraced AI earlier than its competitors and positioned itself as the default backend for AI apps. With support for pgvector, embeddings, and real-time features on top of PostgreSQL, So supabase became extremely attractive for AI startups and developers building LLM-powered applications.

How Supabase works behind the scenes?

Let’s say you’re building a store app and want to query the name and price of products in the “electronics” category.
Here’s what your Supabase client code might look like:

1. This is the supabase query builder from the client-side library where we create the client by providing the project url and a secret key.
   If we want to query data (“name” and “price”) from the products table where products categorized as electronics.
2. At first glance, it feels like you’re writing SQL right in your frontend but there’s a lot happening under the hood.
   

Supabase converts this SQL like syntax of the client library code into a REST call with query parameters. Something like this :

https://[projectId].supabase.co/rest/v1/products?select=name,price&category=eq.electronics

This request first hits Supabase’s API Gateway, which routes it to a service called PostgREST the magic layer that converts your REST query into real SQL for PostgreSQL to execute.

Here’s what that REST call becomes internally:

SELECT name, price FROM products WHERE category = "electronics

On the backend, Supabase uses something called as the Prepared statements, which basically protects the SQL from SQL Injection meaning Supabase parameterizes it to prevent SQL injection attacks. Our constructed query is wrapped around a template like this :

PREPARE product_query(text) AS 
SELECT name, price 
FROM products
WHERE category = $1

EXECUTE product_query('electronics')

Parameterized queries not only improve security but also allow for better caching and performance optimization.

Handling Scale with Connection Pooling

If your app suddenly goes viral and thousands of users start querying at once, creating a new database connection for every request would slow things down fast.

That’s where connection pooling comes in.
Supabase uses pgBouncer, a lightweight PostgreSQL connection pooler, which keeps a pool of open connections ready to be reused.
This ensures queries are handled efficiently no matter how much traffic spikes.

Enforcing Security with Row-Level Security (RLS)

Here’s where things get interesting.

Now, before PostgREST sends the query to PostgreSQL for it to execute, there is one more important layer that comes in, and that is Row Level Security. Now what’s this new thing that everyone’s talking about?

The thing is, PostgREST first has to make sure that whoever is executing this query is actually allowed to read the data or not.

And as we discussed, BaaS does not have a backend as we tend to connect the frontend directly to Supabase. If you don’t have any backend protection layer, what if data is not secure or gets leaked, especially when you try to talk to the DB directly from the frontend? That’s where RLS comes in.

Row level security restricts database operations on a row level.

For example, the policy below states that only authenticated users can read the data from the table.

When an authenticated user calls getProducts(), their JWT token (from Supabase Auth or an external provider like Clerk) is sent along with the request.
Supabase verifies that token before executing the query if the user isn’t authorized, the query never runs.

Once the SQL query executes, PostgREST receives the result from Postgres, converts it into JSON, and returns it to your frontend. And on the frontend the data would be in the same structured format that you’d expect from any modern API.

Supabase manages the complex backend layers for you from authentication and security to query translation and scaling while letting you stay close to SQL. No boilerplate, no infrastructure stress.
You get all the power of PostgreSQL without managing servers, roles, or credentials manually.

No wonder it’s rapidly becoming the go-to backend for SaaS and AI startups.

👉 Explore the Supabase Documentation

Thank you so much for taking the time to read this article. It takes effort to research, write, and break down complex systems like Supabase into something clear and practical, so if this helped you understand it even a little better, that means a lot.

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Stay curious, keep building, and I’ll see you in the next article.