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Storage ⇄ Data warehouse

Amazon S3 to AWS S3 integration — real-time, two-way sync

Keep Amazon S3 and AWS S3 in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon S3 and AWS S3

Bridge query-ready tables and stored files: AWS S3 and Amazon S3 keep the same records in step, in real time, in both directions.

AWS S3 keeps the tables and query results a business reports on; Amazon S3 keeps the raw files, documents, and objects that the same business produces and shares. The two overlap wherever a dataset lives as both — a file dropped in Amazon S3 that has to become rows in AWS S3, or a result in AWS S3 that people downstream need back as a file in Amazon S3. When that overlap is bridged by manual export and import or an overnight job, one side spends the day working from a stale copy.

Stacksync syncs Objects, Prefixes, Object Metadata, Object Versions in AWS S3 with Multipart uploads, Buckets, Objects, Object metadata in Amazon S3 field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set.

Common use cases

  • 01 Ingest partner or vendor file drops (CSV, JSON, Parquet) from a bucket into a database or CRM as records.
  • 02 Export synced operational data to S3 as files feeding a data lake or downstream batch jobs.
  • 03 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.
  • 04 Two-way sync Object tags with a database so retention or classification labels set in an internal app write back onto S3 objects via the tagging API without rewriting the files.

Common sync patterns

One dataset, kept consistent both ways

Where the same dataset lives as a file in Amazon S3 and a table in AWS S3, a change on either side propagates to the other, ending the drift between the file people read and the table people query.

Where Amazon S3 holds the file inventory: make it queryable

The catalog of documents, owners, and folders in Amazon S3 appears as Objects, Prefixes, Object Metadata, Object Versions in AWS S3, so file metadata can be joined against the rest of your data and reported on.

Where AWS S3 computes the labels: push them onto the files

Classifications, scores, or status derived in AWS S3 are written back onto the matching Multipart uploads, Buckets, Objects, Object metadata in Amazon S3 as metadata or tags, so the file store reflects what analytics decided.

What you can sync between Amazon S3 and AWS S3

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 AWS S3 objects How this pairing syncs
Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. Buckets Top-level containers a sync targets; region and policy are set at this level. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
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. Objects The stored files (CSV, JSON, Parquet); syncs read them as datasets or write exports into them. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
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. Object Metadata System and user-defined metadata read alongside object contents. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
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. Object Versions Prior copies retained when versioning is enabled, relevant for reprocessing. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. Prefixes Key-name paths used to partition synced datasets, since S3 has no real directories. Prefixes (folders) is specific to Amazon S3 and Prefixes to AWS S3 — 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. Event Notifications Notifications on object creation or deletion that trigger incremental processing. Multipart uploads is specific to Amazon S3 and Event Notifications to AWS S3 — each maps to any object or custom field on the other side.

How changes propagate between Amazon S3 and AWS S3

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 AWS S3 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 written to AWS S3 through its API, with automatic retries and rate-limit backoff.

AWS S3 Amazon S3 Sub-second propagation

DetectionAWS S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge.

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.
  • AWS S3: Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes.
What ships with Amazon S3 ⇄ AWS S3

Connect Amazon S3 and AWS S3 for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–AWS S3 connection.

Real-time

Two-way sync

Changes in Amazon S3 or AWS S3 instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon S3 or AWS S3 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 AWS S3 record.

Observability

Monitoring

Track your Amazon S3 ⇄ AWS S3 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 AWS S3.

How the Amazon S3 and AWS S3 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.

AWS S3

Integration surface
REST API (the S3 API), accessed directly or through AWS SDKs
Authentication
AWS IAM credentials with SigV4 signing; commonly a role scoped to specific buckets and prefixes
Change detection
S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge; list-based polling as a fallback
Capabilities
read · write · webhooks
Rate limits
Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes
How it works

How to connect Amazon S3 to AWS S3 — 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.

  1. 01

    Connect your apps

    Authenticate Amazon S3 and AWS S3 with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Amazon S3 connected
    AWS S3 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon S3 and AWS S3 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Amazon S3 ⇄ AWS S3
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Amazon S3 AWS S3
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon S3 and AWS S3 integration FAQ

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.

Learn more about security
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 534 integrations available for Amazon S3 and AWS S3.

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