Files
supabase/apps/docs/spec/enrichments/tsdoc_v2/storage.json
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supabase-supabase-autofixer[bot]andsupabase-releaser[bot] af24c397fd docs: update js sdk docs (2.107.0) (#46583)
Updates JS sdk documentation following stable release.
Ran `make` in apps/docs/spec to regenerate tsdoc files.

**Details:**
- **Version:** `2.107.0`
- **Source:** `supabase-js-stable-release`
- **Changes:** Regenerated tsdoc files from latest spec files

🤖 Auto-generated from @supabase/supabase-js stable release.

Co-authored-by: supabase-releaser[bot] <223506987+supabase-releaser[bot]@users.noreply.github.com>
2026-06-02 16:45:59 +02:00

35694 lines
1.4 MiB
Plaintext

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{
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"text": "\n\nResponse:\n"
},
{
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}
]
},
{
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"content": [
{
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},
{
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"text": "`buckets`"
},
{
"kind": "text",
"text": " table permissions: "
},
{
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},
{
"kind": "text",
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},
{
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},
{
"kind": "text",
"text": "\n - "
},
{
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},
{
"kind": "text",
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}
]
}
]
},
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},
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]
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"content": [
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"kind": "text",
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},
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}
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{
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}
]
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{
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"text": "```js\nconst catalog = supabase.storage.analytics.from('analytics-data')\n\n// Drop table with purge option (removes all data)\nconst { error: dropError } = await catalog.dropTable(\n { namespace: ['default'], name: 'events' },\n { purge: true }\n)\n\nif (dropError?.isNotFound()) {\n console.log('Table does not exist')\n}\n\n// Drop namespace (must be empty)\nawait catalog.dropNamespace({ namespace: ['default'] })\n```"
}
]
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"content": [
{
"kind": "text",
"text": "This method provides a bridge between Supabase's bucket management and the standard\nApache Iceberg REST Catalog API. The bucket name maps to the Iceberg warehouse parameter.\nAll authentication and configuration is handled automatically using your Supabase credentials.\n\n**Error Handling**: Invalid bucket names throw immediately. All catalog\noperations return "
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},
{
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},
{
"kind": "code",
"text": "`IcebergRestCatalog`"
},
{
"kind": "text",
"text": " from iceberg-js.\nFor complete API documentation and advanced usage, refer to the\n[iceberg-js documentation](https://supabase.github.io/iceberg-js/)."
}
]
}
],
"modifierTags": ["@alpha"]
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"character": 2,
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],
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{
"id": 101,
"name": "bucketName",
"variant": "param",
"kind": 32768,
"flags": {},
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{
"kind": "text",
"text": "The name of the analytics bucket (warehouse) to connect to"
}
]
},
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"name": "string"
}
}
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}
],
"blockTags": [
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}
]
},
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"content": [
{
"kind": "code",
"text": "```js\nconst { data, error } = await supabase\n .storage\n .analytics\n .listBuckets({\n limit: 10,\n offset: 0,\n sortColumn: 'created_at',\n sortOrder: 'desc'\n })\n```"
},
{
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{
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],
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{
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"text": "\n\nResponse:\n"
},
{
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}
]
},
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"content": [
{
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},
{
"kind": "code",
"text": "`buckets`"
},
{
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},
{
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},
{
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{
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},
{
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"text": "\n - "
},
{
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"text": "`objects`"
},
{
"kind": "text",
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]
}
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},
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]
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}
}
],
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"type": "reference",
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]
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{
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},
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},
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}
]
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}
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"name": "createSignedUrls",
"variant": "signature",
"kind": 4096,
"flags": {},
"comment": {
"summary": [
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],
"blockTags": [
{
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{
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"kind": "text",
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]
},
{
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{
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}
]
},
{
"tag": "@example",
"name": "Create Signed URLs",
"content": [
{
"kind": "code",
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},
{
"kind": "text",
"text": "\n\nResponse:\n"
},
{
"kind": "code",
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}
]
},
{
"tag": "@remarks",
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},
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{
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},
{
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"readme": [
{
"kind": "text",
"text": "<br />\n<p align=\"center\">\n <a href=\"https://supabase.io\">\n <picture>\n <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://raw.githubusercontent.com/supabase/supabase/master/packages/common/assets/images/supabase-logo-wordmark--dark.svg\">\n <source media=\"(prefers-color-scheme: light)\" srcset=\"https://raw.githubusercontent.com/supabase/supabase/master/packages/common/assets/images/supabase-logo-wordmark--light.svg\">\n <img alt=\"Supabase Logo\" width=\"300\" src=\"https://raw.githubusercontent.com/supabase/supabase/master/packages/common/assets/images/logo-preview.jpg\">\n </picture>\n </a>\n\n <h1 align=\"center\">Supabase Storage JS SDK</h1>\n\n <h3 align=\"center\">JavaScript SDK to interact with Supabase Storage, including file storage and vector embeddings.</h3>\n\n <p align=\"center\">\n <a href=\"https://supabase.com/docs/guides/storage\">Guides</a>\n ·\n <a href=\"https://supabase.com/docs/reference/javascript/storage-createbucket\">Reference Docs</a>\n ·\n <a href=\"https://supabase.github.io/supabase-js/storage-js/v2/spec.json\">TypeDoc</a>\n </p>\n</p>\n\n<div align=\"center\">\n\n[![Build](https://github.com/supabase/supabase-js/workflows/CI/badge.svg)](https://github.com/supabase/supabase-js/actions?query=branch%3Amaster)\n[![Package](https://img.shields.io/npm/v/@supabase/storage-js)](https://www.npmjs.com/package/@supabase/storage-js)\n[![License: MIT](https://img.shields.io/npm/l/@supabase/supabase-js)](#license)\n[![pkg.pr.new](https://pkg.pr.new/badge/supabase/storage-js)](https://pkg.pr.new/~/supabase/storage-js)\n\n</div>\n\n## Requirements\n\n- **Node.js 20 or later** (Node.js 18 support dropped as of October 31, 2025)\n- For browser support, all modern browsers are supported\n\n> ⚠️ **Node.js 18 Deprecation Notice**\n>\n> Node.js 18 reached end-of-life on April 30, 2025. As announced in [our deprecation notice](https://github.com/orgs/supabase/discussions/37217), support for Node.js 18 was dropped on October 31, 2025.\n\n## Features\n\n- **File Storage**: Upload, download, list, move, and delete files\n- **Access Control**: Public and private buckets with fine-grained permissions\n- **Signed URLs**: Generate time-limited URLs for secure file access\n- **Image Transformations**: On-the-fly image resizing and optimization\n- **Vector Embeddings**: Store and query high-dimensional embeddings with similarity search\n- **Analytics Buckets**: Iceberg table-based buckets optimized for analytical queries and data processing\n\n## Quick Start Guide\n\n### Installing the module\n\n"
},
{
"kind": "code",
"text": "```bash\nnpm install @supabase/storage-js\n```"
},
{
"kind": "text",
"text": "\n\n### Connecting to the storage backend\n\nThere are two ways to use the Storage SDK:\n\n#### Option 1: Via Supabase Client (Recommended)\n\nIf you're already using "
},
{
"kind": "code",
"text": "`@supabase/supabase-js`"
},
{
"kind": "text",
"text": ", access storage through the client:\n\n"
},
{
"kind": "code",
"text": "```js\nimport { createClient } from '@supabase/supabase-js'\n\n// Use publishable key for frontend applications\nconst supabase = createClient('https://<project_ref>.supabase.co', '<your-publishable-key>')\n\n// Access storage\nconst storage = supabase.storage\n\n// Access different bucket types\nconst regularBucket = storage.from('my-bucket')\nconst vectorBucket = storage.vectors.from('embeddings-bucket')\nconst analyticsBucket = storage.analytics // Analytics API\n```"
},
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"kind": "text",
"text": "\n\n#### Option 2: Standalone StorageClient\n\nFor backend applications or when you need to bypass Row Level Security:\n\n"
},
{
"kind": "code",
"text": "```js\nimport { StorageClient } from '@supabase/storage-js'\n\nconst STORAGE_URL = 'https://<project_ref>.supabase.co/storage/v1'\nconst SERVICE_KEY = '<your-secret-key>' // Use secret key for backend operations\n\nconst storageClient = new StorageClient(STORAGE_URL, {\n apikey: SERVICE_KEY,\n Authorization: `Bearer ${SERVICE_KEY}`,\n})\n\n// Access different bucket types\nconst regularBucket = storageClient.from('my-bucket')\nconst vectorBucket = storageClient.vectors.from('embeddings-bucket')\nconst analyticsBucket = storageClient.analytics // Analytics API\n```"
},
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"kind": "text",
"text": "\n\n> **When to use each approach:**\n>\n> - Use "
},
{
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"text": "`supabase.storage`"
},
{
"kind": "text",
"text": " when working with other Supabase features (auth, database, etc.) in frontend applications\n> - Use "
},
{
"kind": "code",
"text": "`new StorageClient()`"
},
{
"kind": "text",
"text": " for backend applications, Edge Functions, or when you need to bypass RLS policies\n\n> **Note:** Refer to the [Storage Access Control guide](https://supabase.com/docs/guides/storage/access-control) for detailed information on creating RLS policies.\n\n### Understanding Bucket Types\n\nSupabase Storage supports three types of buckets, each optimized for different use cases:\n\n#### 1. Regular Storage Buckets (File Storage)\n\nStandard buckets for storing files, images, videos, and other assets.\n\n"
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"text": "```js\n// Create regular storage bucket\nconst { data, error } = await storageClient.createBucket('my-files', {\n public: false,\n})\n\n// Upload files\nawait storageClient.from('my-files').upload('avatar.png', file)\n```"
},
{
"kind": "text",
"text": "\n\n**Use cases:** User uploads, media assets, documents, backups\n\n#### 2. Vector Buckets (Embeddings Storage)\n\nSpecialized buckets for storing and querying high-dimensional vector embeddings.\n\n"
},
{
"kind": "code",
"text": "```js\n// Create vector bucket\nawait storageClient.vectors.createBucket('embeddings-prod')\n\n// Create index and insert vectors\nconst bucket = storageClient.vectors.from('embeddings-prod')\nawait bucket.createIndex({\n indexName: 'documents',\n dimension: 1536,\n distanceMetric: 'cosine',\n})\n```"
},
{
"kind": "text",
"text": "\n\n**Use cases:** Semantic search, AI-powered recommendations, similarity matching\n\n**[See full Vector Embeddings documentation below](#vector-embeddings)**\n\n#### 3. Analytics Buckets\n\nSpecialized buckets using Apache Iceberg table format, optimized for analytical queries and large-scale data processing.\n\n"
},
{
"kind": "code",
"text": "```js\n// Create analytics bucket\nawait storageClient.analytics.createBucket('analytics-data')\n\n// List analytics buckets\nconst { data, error } = await storageClient.analytics.listBuckets()\n\n// Delete analytics bucket\nawait storageClient.analytics.deleteBucket('analytics-data')\n```"
},
{
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"text": "\n\n**Use cases:** Time-series data, analytical queries, data lakes, large-scale data processing, business intelligence\n\n**[See full Analytics Buckets documentation below](#analytics-buckets)**\n\n---\n\n### Handling resources\n\n#### Handling Storage Buckets\n\n- Create a new Storage bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.createBucket(\n 'test_bucket', // Bucket name (must be unique)\n { public: false } // Bucket options\n )\n ```"
},
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"kind": "text",
"text": "\n\n- Retrieve the details of an existing Storage bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.getBucket('test_bucket')\n ```"
},
{
"kind": "text",
"text": "\n\n- Update a new Storage bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.updateBucket(\n 'test_bucket', // Bucket name\n { public: false } // Bucket options\n )\n ```"
},
{
"kind": "text",
"text": "\n\n- Remove all objects inside a single bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.emptyBucket('test_bucket')\n ```"
},
{
"kind": "text",
"text": "\n\n- Delete an existing bucket (a bucket can't be deleted with existing objects inside it):\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.deleteBucket('test_bucket')\n ```"
},
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"kind": "text",
"text": "\n\n- Retrieve the details of all Storage buckets within an existing project:\n\n "
},
{
"kind": "code",
"text": "```js\n // List all buckets\n const { data, error } = await storageClient.listBuckets()\n\n // List buckets with options (pagination, sorting, search)\n const { data, error } = await storageClient.listBuckets({\n limit: 10,\n offset: 0,\n sortColumn: 'created_at',\n sortOrder: 'desc',\n search: 'prod',\n })\n ```"
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"text": "\n\n#### Handling Files\n\n- Upload a file to an existing bucket:\n\n "
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"kind": "code",
"text": "```js\n const fileBody = ... // load your file here\n\n const { data, error } = await storageClient.from('bucket').upload('path/to/file', fileBody)\n ```"
},
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"kind": "text",
"text": "\n\n > Note: \n > The path in "
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"text": "`data.Key`"
},
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"kind": "text",
"text": " is prefixed by the bucket ID and is not the value which should be passed to the "
},
{
"kind": "code",
"text": "`download`"
},
{
"kind": "text",
"text": " method in order to fetch the file. \n > To fetch the file via the "
},
{
"kind": "code",
"text": "`download`"
},
{
"kind": "text",
"text": " method, use "
},
{
"kind": "code",
"text": "`data.path`"
},
{
"kind": "text",
"text": " and "
},
{
"kind": "code",
"text": "`data.bucketId`"
},
{
"kind": "text",
"text": " as follows:\n >\n > "
},
{
"kind": "code",
"text": "```javascript\n > const { data, error } = await storageClient.from('bucket').upload('/folder/file.txt', fileBody)\n > // check for errors\n > const { data2, error2 } = await storageClient.from(data.bucketId).download(data.path)\n > ```"
},
{
"kind": "text",
"text": "\n\n > Note: The "
},
{
"kind": "code",
"text": "`upload`"
},
{
"kind": "text",
"text": " method also accepts a map of optional parameters. For a complete list see the [Supabase API reference](https://supabase.com/docs/reference/javascript/storage-from-upload).\n\n- Download a file from an exisiting bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.from('bucket').download('path/to/file')\n ```"
},
{
"kind": "text",
"text": "\n\n- List all the files within a bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.from('bucket').list('folder')\n ```"
},
{
"kind": "text",
"text": "\n\n > Note: The "
},
{
"kind": "code",
"text": "`list`"
},
{
"kind": "text",
"text": " method also accepts a map of optional parameters. For a complete list see the [Supabase API reference](https://supabase.com/docs/reference/javascript/storage-from-list).\n\n- Replace an existing file at the specified path with a new one:\n\n "
},
{
"kind": "code",
"text": "```js\n const fileBody = ... // load your file here\n\n const { data, error } = await storageClient\n .from('bucket')\n .update('path/to/file', fileBody)\n ```"
},
{
"kind": "text",
"text": "\n\n > Note: The "
},
{
"kind": "code",
"text": "`upload`"
},
{
"kind": "text",
"text": " method also accepts a map of optional parameters. For a complete list see the [Supabase API reference](https://supabase.com/docs/reference/javascript/storage-from-upload).\n\n- Move an existing file:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient\n .from('bucket')\n .move('old/path/to/file', 'new/path/to/file')\n ```"
},
{
"kind": "text",
"text": "\n\n- Delete files within the same bucket:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.from('bucket').remove(['path/to/file'])\n ```"
},
{
"kind": "text",
"text": "\n\n- Create signed URL to download file without requiring permissions:\n\n "
},
{
"kind": "code",
"text": "```js\n const expireIn = 60\n\n const { data, error } = await storageClient\n .from('bucket')\n .createSignedUrl('path/to/file', expireIn)\n ```"
},
{
"kind": "text",
"text": "\n\n- Retrieve URLs for assets in public buckets:\n\n "
},
{
"kind": "code",
"text": "```js\n const { data, error } = await storageClient.from('public-bucket').getPublicUrl('path/to/file')\n ```"
},
{
"kind": "text",
"text": "\n\n## Analytics Buckets\n\nSupabase Storage provides specialized analytics buckets using Apache Iceberg table format, optimized for analytical workloads and large-scale data processing. These buckets are designed for data lake architectures, time-series data, and business intelligence applications.\n\n### What are Analytics Buckets?\n\nAnalytics buckets use the Apache Iceberg open table format, providing:\n\n- **ACID transactions** for data consistency\n- **Schema evolution** without data rewrites\n- **Time travel** to query historical data\n- **Efficient metadata management** for large datasets\n- **Optimized for analytical queries** rather than individual file operations\n\n### When to Use Analytics Buckets\n\n**Use analytics buckets for:**\n\n- Time-series data (logs, metrics, events)\n- Data lake architectures\n- Business intelligence and reporting\n- Large-scale batch processing\n- Analytical workloads requiring ACID guarantees\n\n**Use regular storage buckets for:**\n\n- User file uploads (images, documents, videos)\n- Individual file management\n- Content delivery\n- Simple object storage needs\n\n### Quick Start\n\nYou can access analytics functionality through the "
},
{
"kind": "code",
"text": "`analytics`"
},
{
"kind": "text",
"text": " property on your storage client:\n\n#### Via Supabase Client\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { createClient } from '@supabase/supabase-js'\n\nconst supabase = createClient('https://your-project.supabase.co', 'your-publishable-key')\n\n// Access analytics operations\nconst analytics = supabase.storage.analytics\n\n// Create an analytics bucket\nconst { data, error } = await analytics.createBucket('analytics-data')\nif (error) {\n console.error('Failed to create analytics bucket:', error.message)\n} else {\n console.log('Created bucket:', data.name)\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Via StorageClient\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { StorageClient } from '@supabase/storage-js'\n\nconst storageClient = new StorageClient('https://your-project.supabase.co/storage/v1', {\n apikey: 'YOUR_API_KEY',\n Authorization: 'Bearer YOUR_TOKEN',\n})\n\n// Access analytics operations\nconst analytics = storageClient.analytics\n\n// Create an analytics bucket\nawait analytics.createBucket('analytics-data')\n```"
},
{
"kind": "text",
"text": "\n\n### API Reference\n\n#### Create Analytics Bucket\n\nCreates a new analytics bucket using Iceberg table format:\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await analytics.createBucket('my-analytics-bucket')\n\nif (error) {\n console.error('Error:', error.message)\n} else {\n console.log('Created bucket:', data)\n}\n```"
},
{
"kind": "text",
"text": "\n\n**Returns:**\n\n"
},
{
"kind": "code",
"text": "```typescript\n{\n data: {\n id: string\n type: 'ANALYTICS'\n format: string\n created_at: string\n updated_at: string\n } | null\n error: StorageError | null\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### List Analytics Buckets\n\nRetrieves all analytics buckets in your project with optional filtering and pagination:\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await analytics.listBuckets({\n limit: 10,\n offset: 0,\n sortColumn: 'created_at',\n sortOrder: 'desc',\n search: 'prod',\n})\n\nif (data) {\n console.log(`Found ${data.length} analytics buckets`)\n data.forEach((bucket) => {\n console.log(`- ${bucket.id} (created: ${bucket.created_at})`)\n })\n}\n```"
},
{
"kind": "text",
"text": "\n\n**Parameters:**\n\n- "
},
{
"kind": "code",
"text": "`limit?: number`"
},
{
"kind": "text",
"text": " - Maximum number of buckets to return\n- "
},
{
"kind": "code",
"text": "`offset?: number`"
},
{
"kind": "text",
"text": " - Number of buckets to skip (for pagination)\n- "
},
{
"kind": "code",
"text": "`sortColumn?: 'id' | 'name' | 'created_at' | 'updated_at'`"
},
{
"kind": "text",
"text": " - Column to sort by\n- "
},
{
"kind": "code",
"text": "`sortOrder?: 'asc' | 'desc'`"
},
{
"kind": "text",
"text": " - Sort direction\n- "
},
{
"kind": "code",
"text": "`search?: string`"
},
{
"kind": "text",
"text": " - Search term to filter bucket names\n\n**Returns:**\n\n"
},
{
"kind": "code",
"text": "```typescript\n{\n data: AnalyticBucket[] | null\n error: StorageError | null\n}\n```"
},
{
"kind": "text",
"text": "\n\n**Example with Pagination:**\n\n"
},
{
"kind": "code",
"text": "```typescript\n// Fetch first page\nconst firstPage = await analytics.listBuckets({\n limit: 100,\n offset: 0,\n sortColumn: 'created_at',\n sortOrder: 'desc',\n})\n\n// Fetch second page\nconst secondPage = await analytics.listBuckets({\n limit: 100,\n offset: 100,\n sortColumn: 'created_at',\n sortOrder: 'desc',\n})\n```"
},
{
"kind": "text",
"text": "\n\n#### Delete Analytics Bucket\n\nDeletes an analytics bucket. The bucket must be empty before deletion.\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await analytics.deleteBucket('old-analytics-bucket')\n\nif (error) {\n console.error('Failed to delete:', error.message)\n} else {\n console.log('Bucket deleted:', data.message)\n}\n```"
},
{
"kind": "text",
"text": "\n\n**Returns:**\n\n"
},
{
"kind": "code",
"text": "```typescript\n{\n data: { message: string } | null\n error: StorageError | null\n}\n```"
},
{
"kind": "text",
"text": "\n\n> **Note:** A bucket cannot be deleted if it contains data. You must empty the bucket first.\n\n#### Get Iceberg Catalog for Advanced Operations\n\nFor advanced operations like creating tables, namespaces, and querying Iceberg metadata, use the "
},
{
"kind": "code",
"text": "`from()`"
},
{
"kind": "text",
"text": " method to get a configured [iceberg-js](https://github.com/supabase/iceberg-js) client:\n\n"
},
{
"kind": "code",
"text": "```typescript\n// Get an Iceberg REST Catalog client for your analytics bucket\nconst catalog = analytics.from('analytics-data')\n\n// Create a namespace\nawait catalog.createNamespace({ namespace: ['default'] }, { properties: { owner: 'data-team' } })\n\n// Create a table with schema\nawait catalog.createTable(\n { namespace: ['default'] },\n {\n name: 'events',\n schema: {\n type: 'struct',\n fields: [\n { id: 1, name: 'id', type: 'long', required: true },\n { id: 2, name: 'timestamp', type: 'timestamp', required: true },\n { id: 3, name: 'user_id', type: 'string', required: false },\n ],\n 'schema-id': 0,\n 'identifier-field-ids': [1],\n },\n 'partition-spec': {\n 'spec-id': 0,\n fields: [],\n },\n 'write-order': {\n 'order-id': 0,\n fields: [],\n },\n properties: {\n 'write.format.default': 'parquet',\n },\n }\n)\n\n// List tables in namespace\nconst tables = await catalog.listTables({ namespace: ['default'] })\nconsole.log(tables) // [{ namespace: ['default'], name: 'events' }]\n\n// Load table metadata\nconst table = await catalog.loadTable({ namespace: ['default'], name: 'events' })\n\n// Update table properties\nawait catalog.updateTable(\n { namespace: ['default'], name: 'events' },\n { properties: { 'read.split.target-size': '134217728' } }\n)\n\n// Drop table\nawait catalog.dropTable({ namespace: ['default'], name: 'events' })\n\n// Drop namespace\nawait catalog.dropNamespace({ namespace: ['default'] })\n```"
},
{
"kind": "text",
"text": "\n\n**Returns:** "
},
{
"kind": "code",
"text": "`IcebergRestCatalog`"
},
{
"kind": "text",
"text": " instance from [iceberg-js](https://github.com/supabase/iceberg-js)\n\n> **Note:** The "
},
{
"kind": "code",
"text": "`from()`"
},
{
"kind": "text",
"text": " method returns an Iceberg REST Catalog client that provides full access to the Apache Iceberg REST API. For complete documentation of available operations, see the [iceberg-js documentation](https://supabase.github.io/iceberg-js/).\n\n### Error Handling\n\nAnalytics buckets use the same error handling pattern as the rest of the Storage SDK:\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await analytics.createBucket('my-bucket')\n\nif (error) {\n console.error('Error:', error.message)\n console.error('Status:', error.status)\n console.error('Status Code:', error.statusCode)\n // Handle error appropriately\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Throwing Errors\n\nYou can configure the client to throw errors instead of returning them:\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst analytics = storageClient.analytics\nanalytics.throwOnError()\n\ntry {\n const { data } = await analytics.createBucket('my-bucket')\n // data is guaranteed to be present\n console.log('Success:', data)\n} catch (error) {\n if (error instanceof StorageApiError) {\n console.error('API Error:', error.statusCode, error.message)\n }\n}\n```"
},
{
"kind": "text",
"text": "\n\n### TypeScript Types\n\nThe library exports TypeScript types for analytics buckets:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport type { AnalyticBucket, BucketType, StorageError } from '@supabase/storage-js'\n\n// AnalyticBucket type\ninterface AnalyticBucket {\n id: string\n type: 'ANALYTICS'\n format: string\n created_at: string\n updated_at: string\n}\n```"
},
{
"kind": "text",
"text": "\n\n### Common Patterns\n\n#### Checking if a Bucket Exists\n\n"
},
{
"kind": "code",
"text": "```typescript\nasync function bucketExists(bucketName: string): Promise<boolean> {\n const { data, error } = await analytics.listBuckets({\n search: bucketName,\n })\n\n if (error) {\n console.error('Error checking bucket:', error.message)\n return false\n }\n\n return data?.some((bucket) => bucket.id === bucketName) ?? false\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Creating Bucket with Error Handling\n\n"
},
{
"kind": "code",
"text": "```typescript\nasync function ensureAnalyticsBucket(bucketName: string) {\n // Try to create the bucket\n const { data, error } = await analytics.createBucket(bucketName)\n\n if (error) {\n // Check if bucket already exists (conflict error)\n if (error.statusCode === '409') {\n console.log(`Bucket '${bucketName}' already exists`)\n return { success: true, created: false }\n }\n\n // Other error occurred\n console.error('Failed to create bucket:', error.message)\n return { success: false, error }\n }\n\n console.log(`Created new bucket: '${bucketName}'`)\n return { success: true, created: true, data }\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Listing All Buckets with Pagination\n\n"
},
{
"kind": "code",
"text": "```typescript\nasync function getAllAnalyticsBuckets() {\n const allBuckets: AnalyticBucket[] = []\n let offset = 0\n const limit = 100\n\n while (true) {\n const { data, error } = await analytics.listBuckets({\n limit,\n offset,\n sortColumn: 'created_at',\n sortOrder: 'desc',\n })\n\n if (error) {\n console.error('Error fetching buckets:', error.message)\n break\n }\n\n if (!data || data.length === 0) {\n break\n }\n\n allBuckets.push(...data)\n\n // If we got fewer results than the limit, we've reached the end\n if (data.length < limit) {\n break\n }\n\n offset += limit\n }\n\n return allBuckets\n}\n```"
},
{
"kind": "text",
"text": "\n\n## Vector Embeddings\n\nSupabase Storage provides built-in support for storing and querying high-dimensional vector embeddings, powered by S3 Vectors. This enables semantic search, similarity matching, and AI-powered applications without needing a separate vector database.\n\n> **Note:** Vector embeddings functionality is available in "
},
{
"kind": "code",
"text": "`@supabase/storage-js`"
},
{
"kind": "text",
"text": " v2.76 and later.\n\n### Features\n\n- **Vector Buckets**: Organize vector indexes into logical containers\n- **Vector Indexes**: Define schemas with configurable dimensions and distance metrics\n- **Batch Operations**: Insert/update/delete up to 500 vectors per request\n- **Similarity Search**: Query for nearest neighbors using cosine, euclidean, or dot product distance\n- **Metadata Filtering**: Store and filter vectors by arbitrary JSON metadata\n- **Pagination**: Efficiently scan large vector datasets\n- **Parallel Scanning**: Distribute scans across multiple workers for high throughput\n- **Cross-platform**: Works in Node.js, browsers, and edge runtimes\n\n### Quick Start\n\nYou can access vector functionality in three ways, depending on your use case:\n\n#### Option 1: Via Supabase Client (Most Common)\n\nIf you're using the full Supabase client:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { createClient } from '@supabase/supabase-js'\n\nconst supabase = createClient('https://your-project.supabase.co', 'your-publishable-key')\n\n// Access vector operations through storage\nconst vectors = supabase.storage.vectors\n\n// Create a vector bucket\nawait vectors.createBucket('embeddings-prod')\n\n// Create an index\nconst bucket = vectors.from('embeddings-prod')\nawait bucket.createIndex({\n indexName: 'documents-openai',\n dataType: 'float32',\n dimension: 1536,\n distanceMetric: 'cosine',\n})\n\n// Insert vectors\nconst index = bucket.index('documents-openai')\nawait index.putVectors({\n vectors: [\n {\n key: 'doc-1',\n data: { float32: [0.1, 0.2, 0.3 /* ...1536 dimensions */] },\n metadata: { title: 'Introduction', category: 'docs' },\n },\n ],\n})\n\n// Query similar vectors\nconst { data, error } = await index.queryVectors({\n queryVector: { float32: [0.15, 0.25, 0.35 /* ...1536 dimensions */] },\n topK: 5,\n returnDistance: true,\n returnMetadata: true,\n})\n\nif (data) {\n data.matches.forEach((match) => {\n console.log(`${match.key}: distance=${match.distance}`)\n console.log('Metadata:', match.metadata)\n })\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Option 2: Via StorageClient\n\nIf you're using the standalone "
},
{
"kind": "code",
"text": "`StorageClient`"
},
{
"kind": "text",
"text": " for storage operations, access vectors through the "
},
{
"kind": "code",
"text": "`vectors`"
},
{
"kind": "text",
"text": " property:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { StorageClient } from '@supabase/storage-js'\n\nconst storageClient = new StorageClient('https://your-project.supabase.co/storage/v1', {\n apikey: 'YOUR_API_KEY',\n Authorization: 'Bearer YOUR_TOKEN',\n})\n\n// Access vector operations\nconst vectors = storageClient.vectors\n\n// Use the same API as shown in Option 1\nawait vectors.createBucket('embeddings-prod')\nconst bucket = vectors.from('embeddings-prod')\n// ... rest of operations\n```"
},
{
"kind": "text",
"text": "\n\n#### Option 3: Standalone Vector Client\n\nFor vector-only applications that don't need regular file storage operations:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { StorageVectorsClient } from '@supabase/storage-js'\n\n// Initialize standalone vector client\nconst vectorClient = new StorageVectorsClient('https://your-project.supabase.co/storage/v1', {\n headers: { Authorization: 'Bearer YOUR_TOKEN' },\n})\n\n// Use the same API as shown in Option 1\nawait vectorClient.createBucket('embeddings-prod')\nconst bucket = vectorClient.from('embeddings-prod')\n// ... rest of operations\n```"
},
{
"kind": "text",
"text": "\n\n> **When to use each approach:**\n>\n> - **Option 1**: When using other Supabase features (auth, database, realtime)\n> - **Option 2**: When working with both file storage and vectors\n> - **Option 3**: For dedicated vector-only applications without file storage\n\n### API Reference\n\n#### Client Initialization\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst vectorClient = new StorageVectorsClient(url, options?)\n```"
},
{
"kind": "text",
"text": "\n\n**Options:**\n\n- "
},
{
"kind": "code",
"text": "`headers?: Record<string, string>`"
},
{
"kind": "text",
"text": " - Custom HTTP headers (e.g., Authorization)\n- "
},
{
"kind": "code",
"text": "`fetch?: Fetch`"
},
{
"kind": "text",
"text": " - Custom fetch implementation\n\n#### Vector Buckets\n\nVector buckets are top-level containers for organizing vector indexes.\n\n##### Create Bucket\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await vectorClient.createBucket('my-bucket')\n```"
},
{
"kind": "text",
"text": "\n\n##### Get Bucket\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await vectorClient.getBucket('my-bucket')\nconsole.log('Created at:', new Date(data.vectorBucket.creationTime! * 1000))\n```"
},
{
"kind": "text",
"text": "\n\n##### List Buckets\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await vectorClient.listBuckets({\n prefix: 'prod-',\n maxResults: 100,\n})\n\n// Pagination\nif (data?.nextToken) {\n const next = await vectorClient.listBuckets({ nextToken: data.nextToken })\n}\n```"
},
{
"kind": "text",
"text": "\n\n##### Delete Bucket\n\n"
},
{
"kind": "code",
"text": "```typescript\n// Bucket must be empty (all indexes deleted first)\nconst { error } = await vectorClient.deleteBucket('my-bucket')\n```"
},
{
"kind": "text",
"text": "\n\n#### Vector Indexes\n\nVector indexes define the schema for embeddings including dimension and distance metric.\n\n##### Create Index\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst bucket = vectorClient.from('my-bucket')\n\nawait bucket.createIndex({\n indexName: 'my-index',\n dataType: 'float32',\n dimension: 1536,\n distanceMetric: 'cosine', // 'cosine' | 'euclidean' | 'dotproduct'\n metadataConfiguration: {\n nonFilterableMetadataKeys: ['raw_text', 'internal_id'],\n },\n})\n```"
},
{
"kind": "text",
"text": "\n\n**Distance Metrics:**\n\n- "
},
{
"kind": "code",
"text": "`cosine`"
},
{
"kind": "text",
"text": " - Cosine similarity (normalized dot product)\n- "
},
{
"kind": "code",
"text": "`euclidean`"
},
{
"kind": "text",
"text": " - Euclidean distance (L2 norm)\n- "
},
{
"kind": "code",
"text": "`dotproduct`"
},
{
"kind": "text",
"text": " - Dot product similarity\n\n##### Get Index\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await bucket.getIndex('my-index')\nconsole.log('Dimension:', data?.index.dimension)\nconsole.log('Distance metric:', data?.index.distanceMetric)\n```"
},
{
"kind": "text",
"text": "\n\n##### List Indexes\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await bucket.listIndexes({\n prefix: 'documents-',\n maxResults: 100,\n})\n```"
},
{
"kind": "text",
"text": "\n\n##### Delete Index\n\n"
},
{
"kind": "code",
"text": "```typescript\n// Deletes index and all its vectors\nawait bucket.deleteIndex('my-index')\n```"
},
{
"kind": "text",
"text": "\n\n#### Vector Operations\n\n##### Insert/Update Vectors (Upsert)\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst index = vectorClient.from('my-bucket').index('my-index')\n\nawait index.putVectors({\n vectors: [\n {\n key: 'unique-id-1',\n data: {\n float32: [\n /* 1536 numbers */\n ],\n },\n metadata: {\n title: 'Document Title',\n category: 'technical',\n page: 1,\n },\n },\n // ... up to 500 vectors per request\n ],\n})\n```"
},
{
"kind": "text",
"text": "\n\n**Limitations:**\n\n- 1-500 vectors per request\n- Vectors must match index dimension\n- Keys must be unique within index\n\n##### Get Vectors by Key\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await index.getVectors({\n keys: ['doc-1', 'doc-2', 'doc-3'],\n returnData: true, // Include embeddings\n returnMetadata: true, // Include metadata\n})\n\ndata?.vectors.forEach((v) => {\n console.log(v.key, v.metadata)\n})\n```"
},
{
"kind": "text",
"text": "\n\n##### Query Similar Vectors (ANN Search)\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await index.queryVectors({\n queryVector: {\n float32: [\n /* 1536 numbers */\n ],\n },\n topK: 10,\n filter: {\n category: 'technical',\n published: true,\n },\n returnDistance: true,\n returnMetadata: true,\n})\n\n// Results ordered by similarity\ndata?.matches.forEach((match) => {\n console.log(`${match.key}: distance=${match.distance}`)\n})\n```"
},
{
"kind": "text",
"text": "\n\n**Filter Syntax:**\nThe "
},
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"kind": "code",
"text": "`filter`"
},
{
"kind": "text",
"text": " parameter accepts arbitrary JSON for metadata filtering. Non-filterable keys (configured at index creation) cannot be used in filters but can still be returned.\n\n##### List/Scan Vectors\n\n"
},
{
"kind": "code",
"text": "```typescript\n// Simple pagination\nlet nextToken: string | undefined\ndo {\n const { data } = await index.listVectors({\n maxResults: 500,\n nextToken,\n returnMetadata: true,\n })\n\n console.log('Batch:', data?.vectors.length)\n nextToken = data?.nextToken\n} while (nextToken)\n\n// Parallel scanning (4 workers)\nconst workers = [0, 1, 2, 3].map(async (segmentIndex) => {\n const { data } = await index.listVectors({\n segmentCount: 4,\n segmentIndex,\n returnMetadata: true,\n })\n return data?.vectors || []\n})\n\nconst results = await Promise.all(workers)\nconst allVectors = results.flat()\n```"
},
{
"kind": "text",
"text": "\n\n**Limitations:**\n\n- "
},
{
"kind": "code",
"text": "`maxResults`"
},
{
"kind": "text",
"text": ": 1-1000 (default: 500)\n- "
},
{
"kind": "code",
"text": "`segmentCount`"
},
{
"kind": "text",
"text": ": 1-16\n- Response may be limited by 1MB size\n\n##### Delete Vectors\n\n"
},
{
"kind": "code",
"text": "```typescript\nawait index.deleteVectors({\n keys: ['doc-1', 'doc-2', 'doc-3'],\n // ... up to 500 keys per request\n})\n```"
},
{
"kind": "text",
"text": "\n\n### Error Handling\n\nThe library uses a consistent error handling pattern:\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst { data, error } = await vectorClient.createBucket('my-bucket')\n\nif (error) {\n console.error('Error:', error.message)\n console.error('Status:', error.status)\n console.error('Code:', error.statusCode)\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Error Codes\n\n| Code | HTTP | Description |\n| ---------------------------- | ---- | ----------------------- |\n| "
},
{
"kind": "code",
"text": "`InternalError`"
},
{
"kind": "text",
"text": " | 500 | Internal server error |\n| "
},
{
"kind": "code",
"text": "`S3VectorConflictException`"
},
{
"kind": "text",
"text": " | 409 | Resource already exists |\n| "
},
{
"kind": "code",
"text": "`S3VectorNotFoundException`"
},
{
"kind": "text",
"text": " | 404 | Resource not found |\n| "
},
{
"kind": "code",
"text": "`S3VectorBucketNotEmpty`"
},
{
"kind": "text",
"text": " | 400 | Bucket contains indexes |\n| "
},
{
"kind": "code",
"text": "`S3VectorMaxBucketsExceeded`"
},
{
"kind": "text",
"text": " | 400 | Bucket quota exceeded |\n| "
},
{
"kind": "code",
"text": "`S3VectorMaxIndexesExceeded`"
},
{
"kind": "text",
"text": " | 400 | Index quota exceeded |\n\n#### Throwing Errors\n\nYou can configure the client to throw errors instead:\n\n"
},
{
"kind": "code",
"text": "```typescript\nconst vectorClient = new StorageVectorsClient(url, options)\nvectorClient.throwOnError()\n\ntry {\n const { data } = await vectorClient.createBucket('my-bucket')\n // data is guaranteed to be present\n} catch (error) {\n if (error instanceof StorageVectorsApiError) {\n console.error('API Error:', error.statusCode)\n }\n}\n```"
},
{
"kind": "text",
"text": "\n\n### Advanced Usage\n\n#### Scoped Clients\n\nCreate scoped clients for cleaner code:\n\n"
},
{
"kind": "code",
"text": "```typescript\n// Bucket-scoped operations\nconst bucket = vectorClient.from('embeddings-prod')\nawait bucket.createIndex({\n /* ... */\n})\nawait bucket.listIndexes()\n\n// Index-scoped operations\nconst index = bucket.index('documents-openai')\nawait index.putVectors({\n /* ... */\n})\nawait index.queryVectors({\n /* ... */\n})\n```"
},
{
"kind": "text",
"text": "\n\n#### Custom Fetch\n\nProvide a custom fetch implementation:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { StorageVectorsClient } from '@supabase/storage-js'\n\nconst vectorClient = new StorageVectorsClient(url, {\n fetch: customFetch,\n headers: {\n /* ... */\n },\n})\n```"
},
{
"kind": "text",
"text": "\n\n#### Batch Processing\n\nProcess large datasets in batches:\n\n"
},
{
"kind": "code",
"text": "```typescript\nasync function insertLargeDataset(vectors: VectorObject[]) {\n const batchSize = 500\n\n for (let i = 0; i < vectors.length; i += batchSize) {\n const batch = vectors.slice(i, i + batchSize)\n await index.putVectors({ vectors: batch })\n console.log(`Inserted ${i + batch.length}/${vectors.length}`)\n }\n}\n```"
},
{
"kind": "text",
"text": "\n\n#### Float32 Validation\n\nEnsure vectors are properly normalized to float32:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport { normalizeToFloat32 } from '@supabase/storage-js'\n\nconst vector = normalizeToFloat32([0.1, 0.2, 0.3 /* ... */])\n```"
},
{
"kind": "text",
"text": "\n\n### Type Definitions\n\nThe library exports comprehensive TypeScript types:\n\n"
},
{
"kind": "code",
"text": "```typescript\nimport type {\n VectorBucket,\n VectorIndex,\n VectorData,\n VectorObject,\n VectorMatch,\n VectorMetadata,\n DistanceMetric,\n ApiResponse,\n StorageVectorsError,\n} from '@supabase/storage-js'\n```"
},
{
"kind": "text",
"text": "\n\n## Development\n\nThis package is part of the [Supabase JavaScript monorepo](https://github.com/supabase/supabase-js). To work on this package:\n\n### Building\n\n#### Build Scripts Overview\n\n"
},
{
"kind": "code",
"text": "```bash\n# Build the package\npnpm nx build storage-js\n\n# Watch mode for development\npnpm nx build storage-js --watch\n\n# Generate documentation\npnpm nx docs storage-js\n```"
},
{
"kind": "text",
"text": "\n\n### Testing\n\n**Important:** The storage-js tests require a local Supabase stack running via the Supabase CLI. Docker must be running since the Supabase CLI uses it internally.\n\n#### Prerequisites\n\n1. **Docker** must be installed and running (used by Supabase CLI internally)\n2. **Supabase CLI** — installed automatically via "
},
{
"kind": "code",
"text": "`pnpm exec supabase`"
},
{
"kind": "text",
"text": "\n\n#### Test Scripts Overview\n\n| Script | Description | What it does |\n| ----------------- | --------------------------------- | ----------------------------------------------------------------- |\n| "
},
{
"kind": "code",
"text": "`test:storage`"
},
{
"kind": "text",
"text": " | **Complete test workflow** | Runs the full test cycle: clean → start infra → run tests → clean |\n| "
},
{
"kind": "code",
"text": "`test:suite`"
},
{
"kind": "text",
"text": " | **Jest tests only** | Runs Jest tests with coverage (requires infra to be running) |\n| "
},
{
"kind": "code",
"text": "`test:infra`"
},
{
"kind": "text",
"text": " | **Start test infrastructure** | Starts Supabase CLI stack (PostgreSQL, Storage API, Kong, etc.) |\n| "
},
{
"kind": "code",
"text": "`test:clean-post`"
},
{
"kind": "text",
"text": " | **Stop and clean infrastructure** | Stops the Supabase CLI stack |\n\n#### Running Tests\n\n##### Option 1: Complete Test Run (Recommended)\n\nThis handles everything automatically - starting infrastructure, running tests, and cleaning up:\n\n"
},
{
"kind": "code",
"text": "```bash\n# From monorepo root\npnpm nx test:storage storage-js\n```"
},
{
"kind": "text",
"text": "\n\nThis command will:\n\n1. Stop any existing test containers\n2. Build and start fresh test infrastructure\n3. Wait for services to be ready\n4. Run all Jest tests with coverage\n5. Clean up all containers after tests complete\n\n##### Option 2: Manual Infrastructure Management\n\nUseful for development when you want to run tests multiple times without restarting Docker:\n\n"
},
{
"kind": "code",
"text": "```bash\n# Step 1: Start the test infrastructure\n# From root\npnpm nx test:infra storage-js\n# This starts: PostgreSQL, Storage API, Kong Gateway, and imgproxy\n\n# Step 2: Run tests (can run multiple times)\npnpm nx test:suite storage-js\n\n# Step 3: When done, clean up the infrastructure\npnpm nx test:clean-post storage-js\n```"
},
{
"kind": "text",
"text": "\n\n##### Option 3: Development Mode\n\nFor actively developing and debugging tests:\n\n"
},
{
"kind": "code",
"text": "```bash\n# Start infrastructure once (from root)\npnpm nx test:infra storage-js\n\n# Run tests in watch mode\npnpm nx test:suite storage-js --watch\n\n# Clean up when done\npnpm nx test:clean-post storage-js\n```"
},
{
"kind": "text",
"text": "\n\n#### Test Infrastructure Details\n\nThe test infrastructure is managed via the Supabase CLI ("
},
{
"kind": "code",
"text": "`pnpm exec supabase start --workdir test`"
},
{
"kind": "text",
"text": "), which starts a local Supabase stack defined by the config in "
},
{
"kind": "code",
"text": "`test/`"
},
{
"kind": "text",
"text": ". This includes PostgreSQL, the Storage API, Kong Gateway, and supporting services.\n\n#### Common Issues and Solutions\n\n| Issue | Solution |\n| --------------------------------- | ------------------------------------------------------------------------------------------------- |\n| Port conflicts | Another service is using a required port. Run "
},
{
"kind": "code",
"text": "`pnpm nx test:clean-post storage-js`"
},
{
"kind": "text",
"text": " then try again |\n| \"request failed, reason:\" errors | Infrastructure isn't running. Run "
},
{
"kind": "code",
"text": "`pnpm nx test:infra storage-js`"
},
{
"kind": "text",
"text": " first |\n| Tests fail with connection errors | Ensure Docker is running (Supabase CLI requires Docker) |\n| Stack already running | Run "
},
{
"kind": "code",
"text": "`pnpm nx test:clean-post storage-js`"
},
{
"kind": "text",
"text": " to stop it before restarting |\n\n#### Understanding Test Failures\n\n- **StorageUnknownError with \"request failed\"**: Infrastructure not running\n- **Snapshot failures**: Expected test data has changed — review and update snapshots if needed\n\n### Contributing\n\nWe welcome contributions! Please see our [Contributing Guide]("
},
{
"kind": "relative-link",
"text": "../../../CONTRIBUTING.md",
"target": 11
},
{
"kind": "text",
"text": ") for details on how to get started.\n\nFor major changes or if you're unsure about something, please open an issue first to discuss your proposed changes."
}
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