Real-time
Two-way sync
Changes in Amazon S3 or Supabase instantly reflect in both systems. No stale data, no manual imports.
Storage ⇄ Database
Amazon S3 to Supabase integration — real-time, two-way sync
Keep Amazon S3 and Supabase in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Amazon S3 and Supabase
Keep Supabase and Amazon S3 in step: a row in Supabase for every file in Amazon S3, with names, paths, metadata, and status staying consistent in real time, in both directions.
A database holds structured records; a storage system holds the files those records depend on, such as contracts, images, exports, uploads, and documents. The two describe the same things from opposite sides: a row in Supabase says a file exists and carries its name, location, and status, while Amazon S3 holds the bytes. Linked only by a hand-kept path or a one-off script, the two drift the moment a file is renamed, moved, or deleted and the record still points at where it used to be.
Stacksync syncs Storage Object Metadata, Tables, Views, Schemas in Supabase with Buckets, Objects, Object metadata, Object tags in Amazon S3 bi-directionally and in real time. File attributes, including name, path or object key, size, type, modified time, owner, and tags or custom properties, map field by field to columns on the matching row, and a change on either side shows up on the other within seconds. New files appear as rows, metadata edits travel in the direction you choose, and deletes stay consistent, with conflict rules you set in place of nightly reconciliation scripts.
Common use cases
- 01 Consolidate Supabase project data into a warehouse for analytics while keeping the app database as the system of record
- 02 Sync application tables in Supabase with the CRM two-way so new signups appear as contacts and sales edits flow back to the app
- 03 Reconcile Object versions and delete markers into an audit table so teams track when files under a compliance prefix were added, replaced, or removed.
- 04 Index every new Object's key, size, LastModified, and user metadata into a Postgres catalog table so applications query S3 contents in SQL instead of paging ListObjectsV2.
Common sync patterns
Continuous archival to file storage
Rows from Supabase are written out to Amazon S3 as files on a schedule or as they change, giving a durable, low-cost copy for backup, compliance, or a data lake, without a custom export job to maintain.
A queryable index of the file store
Every file or object in Amazon S3 shows up as a row in Supabase, with its name, folder or key, size, type, and modified date as columns, so the contents of the store can be listed, filtered, and joined like any other table.
File metadata kept in step
Tags, custom properties, owner, or status columns edited on a row in Supabase write back to the matching file's metadata in Amazon S3, and metadata changed in Amazon S3 updates the row, so the two never disagree about a file.
What you can sync between Amazon S3 and Supabase
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| Amazon S3 objects | Supabase objects | How this pairing syncs | |
|---|---|---|---|
| Objects Files stored under a key; content is read with GET and written with PUT, and each object's key/size/ETag/LastModified is the unit indexed into a database. | JSONB Columns Semi-structured payloads such as event properties or nested objects. | Objects is specific to Amazon S3 and JSONB Columns to Supabase — each maps to any object or custom field on the other side. | |
| Object metadata System metadata (Content-Type, size, ETag, LastModified) plus user-defined x-amz-meta-* headers; user metadata is fixed at write time and only changeable by rewriting the object. | Database Functions Postgres functions that can transform or validate synced rows. | Object metadata is specific to Amazon S3 and Database Functions to Supabase — each maps to any object or custom field on the other side. | |
| Object tags Up to 10 key-value tags per object, mutable in place via the tagging API independent of content, so classification and retention labels sync two-way without rewriting files. | Storage Object Metadata File metadata rows that can be joined to synced application data. | Object tags is specific to Amazon S3 and Storage Object Metadata to Supabase — each maps to any object or custom field on the other side. | |
| Object versions When bucket versioning is enabled every write creates a new version ID; prior versions and delete markers are readable for history and audit syncs. | Tables Standard Postgres tables; the primary two-way sync target. | Object versions is specific to Amazon S3 and Tables to Supabase — each maps to any object or custom field on the other side. | |
| Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. | Views Read-side projections exposed to outbound syncs. | Prefixes (folders) is specific to Amazon S3 and Views to Supabase — each maps to any object or custom field on the other side. | |
| Multipart uploads In-progress large-object uploads assembled from parts; objects above ~100 MB (required above 5 GB) are written this way, and incomplete uploads persist until completed or aborted. | Schemas Namespaces (public and custom) that scope sync access. | Multipart uploads is specific to Amazon S3 and Schemas to Supabase — each maps to any object or custom field on the other side. |
How changes propagate between Amazon S3 and Supabase
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
Amazon S3 Supabase Sub-second propagation
DetectionAmazon S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge.
DeliveryEach detected change is applied to Supabase as a row-level write, with types converted between the two schemas.
Supabase Amazon S3 Sub-second propagation
DetectionSupabase pushes changes as they happen — webhook events backed by change data capture. Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime.
DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Amazon S3: S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.
- Supabase: SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits.
What ships with Amazon S3 ⇄ Supabase
Connect Amazon S3 and Supabase for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–Supabase connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon S3 or Supabase data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single Amazon S3 or Supabase record.
Observability
Monitoring
Track your Amazon S3 ⇄ Supabase sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Amazon S3 and Supabase.
How the Amazon S3 and Supabase connectors work
Amazon S3
- Integration surface
- S3 REST API (also via AWS SDKs and the S3-compatible endpoint)
- Authentication
- AWS IAM credentials — an access key ID and secret access key signed with AWS Signature Version 4; supports temporary STS credentials and cross-account IAM roles
- Change detection
- S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge; there is no modified-since query, so polling relies on each object's LastModified from ListObjectsV2
- Capabilities
- read · write · webhooks
- Rate limits
- S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.
Supabase
- Integration surface
- Direct PostgreSQL wire protocol connection, plus an auto-generated REST API (PostgREST)
- Authentication
- Database credentials (connection string) for SQL access; API keys (anon / service role) for the REST layer
- Change detection
- Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime; database webhooks can also fire on row changes
- Capabilities
- read · write · CDC · webhooks
- Rate limits
- SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits
How it works
How to connect Amazon S3 to Supabase — three steps, no code
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
- 01
Connect your apps
Authenticate Amazon S3 and Supabase with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Amazon S3
connected
Supabase
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon S3 and Supabase objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
objects · Amazon S3 ⇄ SupabaseCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Amazon S3 SupabaseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon S3 and Supabase integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Amazon S3 and Supabase: authenticate both systems, choose the objects to sync (such as Amazon S3's Objects and Object metadata), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the Supabase side: Storage Object Metadata, Tables, Views, Schemas, plus custom fields where Supabase exposes them. On the Amazon S3 side: Buckets, Objects, Object metadata, Object tags. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Amazon S3 and Supabase: Continuous archival to file storage; A queryable index of the file store; File metadata kept in step. Rows from Supabase are written out to Amazon S3 as files on a schedule or as they change, giving a durable, low-cost copy for backup, compliance, or a data lake, without a custom export job to maintain.
-
Amazon S3: S3 REST API (also via AWS SDKs and the S3-compatible endpoint). Authentication: AWS IAM credentials — an access key ID and secret access key signed with AWS Signature Version 4; supports temporary STS credentials and cross-account IAM roles. Supabase: Direct PostgreSQL wire protocol connection, plus an auto-generated REST API (PostgREST). Authentication: Database credentials (connection string) for SQL access; API keys (anon / service role) for the REST layer. Stacksync manages authentication, retries, and rate limits on both sides.
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Supabase: PostgREST auto-generates a REST endpoint per table, with Row Level Security policies gating access at the row level. Amazon S3: Objects can be up to 5 TB, but a single PUT is capped at 5 GB, so larger files must use multipart upload, and objects in Glacier storage classes must be restored before their bytes can be read. Stacksync's field mapping accounts for these differences between Amazon S3 and Supabase without custom code.
SECURITY
Security teams trust Stacksync
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
Every pair below is a real-time, two-way sync. Search all 531 integrations available for Amazon S3 and Supabase.
Popular · 7 of 531
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Amazon S3 ⇄ PostgreSQL -
Amazon S3 ⇄ Amazon RDS -
Amazon S3 ⇄ MySQL -
Amazon S3 ⇄ MariaDB -
Supabase ⇄ Egnyte -
Supabase ⇄ Box -
Supabase ⇄ Sharepoint
No integrations match .
