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Data warehouse ⇄ Storage

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

Keep Amazon Redshift 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.

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

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Why teams connect Amazon Redshift and Amazon S3

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

Amazon Redshift 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 Amazon Redshift, or a result in Amazon Redshift 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 Users and Groups, Databases, Schemas, Tables in Amazon Redshift 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 Centralize CRM, ERP, and product data in Redshift so analysts join it with warehouse tables.
  • 02 Publish finance rollups computed in Redshift back to spreadsheets or operational tools.
  • 03 Mirror Objects under a given Bucket and prefix into another bucket, region, or a warehouse external stage for backup or downstream processing.
  • 04 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.

Common sync patterns

Where Amazon Redshift computes the labels: push them onto the files

Classifications, scores, or status derived in Amazon Redshift 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.

Where Amazon S3 receives the raw files: land them as query-ready rows

Files and exports that arrive in Amazon S3 are parsed into Users and Groups, Databases, Schemas, Tables in Amazon Redshift as they land, so analysts query current data instead of waiting on the next scheduled load.

Where Amazon S3 is the shared drive: publish results back as files

Curated tables and query results from Amazon Redshift are written to Amazon S3 as files the rest of the business can open, keeping the shared copy current without a hand-run export.

What you can sync between Amazon Redshift 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 Redshift objects Amazon S3 objects How this pairing syncs
Views SQL views readable as modeled sources for reverse syncs. Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. Views is specific to Amazon Redshift and Buckets to Amazon S3 — each maps to any object or custom field on the other side.
Materialized Views Precomputed results that downstream syncs can read for performance. 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. Materialized Views is specific to Amazon Redshift and Objects to Amazon S3 — each maps to any object or custom field on the other side.
External Tables (Spectrum) S3-backed tables queryable through Redshift, readable in syncs. 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. External Tables (Spectrum) is specific to Amazon Redshift and Object metadata to Amazon S3 — each maps to any object or custom field on the other side.
Stored Procedures SQL procedures sometimes invoked around load steps. 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. Stored Procedures is specific to Amazon Redshift and Object tags to Amazon S3 — each maps to any object or custom field on the other side.
Users and Groups Principals used to grant a sync connection scoped access. 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. Users and Groups is specific to Amazon Redshift and Object versions to Amazon S3 — each maps to any object or custom field on the other side.
Databases Top-level containers within a cluster or serverless workgroup. 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 Redshift and Prefixes (folders) to Amazon S3 — each maps to any object or custom field on the other side.

How changes propagate between Amazon Redshift 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 Redshift Amazon S3 Interval-based propagation

DetectionStacksync polls Amazon Redshift for changes on an incremental schedule, reading only records changed since the previous pass. Polling or query-based diffing.

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

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

Rate-limit considerations

  • Amazon Redshift: Bounded by cluster or serverless capacity and concurrency settings rather than API quotas.
  • 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 Redshift ⇄ Amazon S3

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

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

Real-time

Two-way sync

Changes in Amazon Redshift 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 Redshift 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 Redshift or Amazon S3 record.

Observability

Monitoring

Track your Amazon Redshift ⇄ 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 Redshift and Amazon S3.

How the Amazon Redshift and Amazon S3 connectors work

Amazon Redshift

Integration surface
SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS
Authentication
Database credentials or IAM-based authentication
Change detection
Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers
Capabilities
read · write
Rate limits
Bounded by cluster or serverless capacity and concurrency settings rather than API quotas

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

    Choose tables

    Pick the Amazon Redshift 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 Redshift ⇄ 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 Redshift Amazon S3
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Redshift 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
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→ 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 533 integrations available for Amazon Redshift and Amazon S3.

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