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supabase/apps/docs/content/guides/storage.mdx
2026-06-01 15:55:06 +02:00

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---
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">
<div className="col-span-12">
<Link
href="https://github.com/supabase/supabase/tree/master/examples/storage/resumable-upload-uppy"
passHref
>
<GlassPanel
icon={'/docs/img/icons/github-icon'}
hasLightIcon={true}
title="Resumable Uploads with Uppy"
>
Use Uppy to upload files to Supabase Storage using the TUS protocol (resumable uploads).
</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">
<div className="col-span-6">
<Link href="https://github.com/supabase/storage-api" passHref>
<GlassPanel title="Supabase Storage API">View the source code.</GlassPanel>
</Link>
</div>
<div className="col-span-6">
<Link href="https://supabase.github.io/storage/" passHref>
<GlassPanel title="OpenAPI Spec">
See the Swagger Documentation for Supabase Storage.
</GlassPanel>
</Link>
</div>
</div>