Skip to content
Database ⇄ Data warehouse

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

Keep Amazon Aurora 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.

  • 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 Aurora and AWS S3

Connect Amazon Aurora and AWS S3 with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Amazon Aurora's rows in AWS S3, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Amazon Aurora where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Amazon Aurora sync into AWS S3 in real time, and result tables in AWS S3 sync back into Amazon Aurora, with schema and type mapping between the two systems handled for you.

Common use cases

  • Stage bulk loads for warehouses that ingest from object storage.
  • Archive change history from ongoing syncs as timestamped files for audit and replay.
  • Offload sync reads to Aurora reader endpoints to avoid load on the writer instance.
  • Two-way sync between Aurora application tables and a CRM so product data and account data stay consistent.

Operational data in the warehouse, minus the pipeline

Rows from Amazon Aurora land in AWS S3 as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in AWS S3 sync into Amazon Aurora, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

What you can sync between Amazon Aurora 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 Aurora objects AWS S3 objects
Databases Logical databases within a cluster that scope a sync connection. Object Versions Prior copies retained when versioning is enabled, relevant for reprocessing.
Schemas Namespaces (PostgreSQL) or database-level grouping (MySQL) used in table selection. Event Notifications Notifications on object creation or deletion that trigger incremental processing.
Tables Relational tables synced bi-directionally at row level. Access Points Scoped network endpoints used to grant a sync narrow access to a bucket.
Views Read-only query-backed sources for downstream syncs. Multipart Uploads The mechanism used to write large export files reliably.
Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. Buckets Top-level containers a sync targets; region and policy are set at this level.
Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. Objects The stored files (CSV, JSON, Parquet); syncs read them as datasets or write exports into them.
What ships with Amazon Aurora ⇄ AWS S3

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

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

Real-time

Two-way sync

Changes in Amazon Aurora 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 Aurora 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 Aurora or AWS S3 record.

Observability

Monitoring

Track your Amazon Aurora ⇄ 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 Aurora and AWS S3.

How the Amazon Aurora and AWS S3 connectors work

Amazon Aurora

Integration surface
MySQL or PostgreSQL wire protocol (SQL); optional RDS Data API over HTTPS
Authentication
Database credentials or IAM database authentication
Change detection
Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters; polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits for wire-protocol access; throughput is bounded by instance class and connection limits

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

    Choose tables

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

Amazon Aurora and AWS S3 integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for Amazon Aurora and AWS S3.

Popular · 8 of 386
All Amazon Aurora integrations All AWS 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