---
id: 'storage'
title: 'Storage'
description: 'Use Supabase to store and serve files.'
subtitle: 'Use Supabase to store and serve files.'
sidebar_label: 'Overview'
hideToc: true
---

Supabase Storage is a robust, scalable solution for managing files of any size with fine-grained access controls and optimized delivery. Whether you're storing user-generated content, analytics data, or vector embeddings, Supabase Storage provides specialized bucket types to meet your specific needs.

## Key features

- **Multi Protocol** - S3 compatible Storage, RESTful API, TUS resumable uploads
- **Global CDN** - Serve your assets with lightning-fast performance from over 285 cities worldwide
- **Image Optimization** - Resize, compress, and transform media files on the fly with built-in image processing
- **Fine-grained Access Control** - Manage file permissions with row-level security and custom policies
- **Multiple Bucket Types** - Specialized storage solutions for different use cases

## Storage bucket types

Supabase Storage offers different bucket types optimized for specific use cases:

### Files buckets

Store and serve traditional files including images, videos, documents, and general-purpose content. Ideal for user-generated content, media libraries, and asset management.

**Use cases:** Images, videos, documents, PDFs, archives

**Features:**

- Global CDN delivery
- Image optimization and transformation
- Row-level security integration
- Direct URL access for files

[Learn more about Files Buckets](/docs/guides/storage/quickstart)

### Analytics buckets

Purpose-built for storing and analyzing data in open table formats like Apache Iceberg. Perfect for time-series data, logs, and large-scale analytical workloads.

**Use cases:** Data lakes, analytics pipelines, ETL operations, historical data analysis

**Features:**

- Apache Iceberg table format support
- SQL-accessible via Postgres foreign tables
- Partitioned data organization
- Efficient data querying and transformation

[Learn more about Analytics Buckets](/docs/guides/storage/analytics/introduction)

### Vector buckets

Specialized storage for vector embeddings and similarity search operations. Designed for AI and ML applications requiring semantic search capabilities.

**Use cases:** AI-powered search, semantic similarity matching, embedding storage, RAG systems

**Features:**

- Optimized vector indexing (HNSW, Flat)
- Multiple distance metrics (cosine, euclidean, L2)
- Metadata filtering for vectors
- Similarity search queries

[Learn more about Vector Buckets](/docs/guides/storage/vector/introduction)

## Examples

Check out all of the Storage [templates and examples](https://github.com/supabase/supabase/tree/master/examples/storage) in our GitHub repository.

<div className="grid md:grid-cols-12 gap-4 not-prose">
  {storageExamples.map((x) => (
    <div className="col-span-12" key={x.href}>
      <Link href={x.href} passHref>
        <GlassPanel icon={'/docs/img/icons/github-icon'} hasLightIcon={true} title={x.name}>
          {x.description}
        </GlassPanel>
      </Link>
    </div>
  ))}
</div>

## Resources

Find the source code and documentation in the Supabase GitHub repository.

<div className="grid md:grid-cols-12 gap-4 not-prose">
  {[
    {
      name: 'Supabase Storage API',
      description: 'View the source code.',
      href: 'https://github.com/supabase/storage-api',
    },
    {
      name: 'OpenAPI Spec',
      description: 'See the Swagger Documentation for Supabase Storage.',
      href: 'https://supabase.github.io/storage/',
    },
  ].map((x) => (
    <div className="col-span-6" key={x.href}>
      <Link href={x.href} passHref>
        <GlassPanel title={x.name}>{x.description}</GlassPanel>
      </Link>
    </div>
  ))}
</div>