Skip to content
Database ⇄ Storage

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

Keep Amazon RDS and Amazon 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.

  • 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

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Amazon RDS and Amazon S3

Keep Amazon RDS and Amazon S3 in step: a row in Amazon RDS 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 Amazon RDS 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 Stored Procedures, Databases, Schemas, Tables in Amazon RDS with Objects, Object metadata, Object tags, Object versions 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 Keep an RDS reporting database hydrated from operational tools without maintaining ETL jobs
  • 02 Sync master data (customers, products, pricing) from an ERP into the RDS databases that power customer-facing apps
  • 03 Trigger a database or ERP record update the moment an S3 Event Notification fires an object-created event, for example when a partner drops an EDI or invoice file into an inbound prefix.
  • 04 Reconcile Object versions and delete markers into an audit table so teams track when files under a compliance prefix were added, replaced, or removed.

Common sync patterns

A landing zone for incoming files

Files that arrive in a folder or bucket in Amazon S3 become rows in Amazon RDS as they land, so a database-driven process can pick them up without polling the storage system's API.

Continuous archival to file storage

Rows from Amazon RDS 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 Amazon RDS, 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.

What you can sync between Amazon RDS and Amazon 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 RDS objects Amazon S3 objects How this pairing syncs
Stored Procedures Engine-specific logic that can react to synced rows. 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. Stored Procedures is specific to Amazon RDS and Object versions to Amazon S3 — each maps to any object or custom field on the other side.
Databases Engine-level databases on the instance that scope a sync's reads and writes. Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. Databases is specific to Amazon RDS and Prefixes (folders) to Amazon S3 — each maps to any object or custom field on the other side.
Schemas Namespaces within a database used to isolate synced tables. 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 is specific to Amazon RDS and Multipart uploads to Amazon S3 — each maps to any object or custom field on the other side.
Tables The core sync target; rows map to records in connected SaaS systems. Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. Tables is specific to Amazon RDS and Buckets to Amazon S3 — each maps to any object or custom field on the other side.
Views Read-side projections exposed to outbound 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. Views is specific to Amazon RDS and Objects to Amazon S3 — each maps to any object or custom field on the other side.
Columns Field-level mapping targets, typed per the underlying engine. 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. Columns is specific to Amazon RDS and Object metadata to Amazon S3 — each maps to any object or custom field on the other side.

How changes propagate between Amazon RDS and Amazon 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 RDS Amazon S3 Sub-second propagation

DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.

DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.

Amazon S3 Amazon RDS 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 Amazon RDS as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Amazon RDS: No API rate limits; throughput depends on instance class, storage IOPS, and connection limits.
  • 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.
What ships with Amazon RDS ⇄ Amazon S3

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

Track your Amazon RDS ⇄ Amazon 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 RDS and Amazon S3.

How the Amazon RDS and Amazon S3 connectors work

Amazon RDS

Integration surface
SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle)
Authentication
Database credentials over SSL/TLS, or IAM database authentication on supported engines
Change detection
Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC; enabled through RDS parameter groups, with polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance class, storage IOPS, and connection limits

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.
How it works

How to connect Amazon RDS to Amazon 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 RDS and Amazon 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 RDS connected
    Amazon S3 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon RDS and Amazon 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 RDS ⇄ Amazon 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 RDS Amazon S3
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Amazon RDS and Amazon 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 445 integrations available for Amazon RDS and Amazon S3.

Popular · 7 of 445
All Amazon RDS integrations All Amazon S3 integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own