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Data warehouse ⇄ Database

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

Keep Amazon Redshift and MySQL 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 MySQL

Connect MySQL and Amazon Redshift 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 MySQL's rows in Amazon Redshift, 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 MySQL where the services that read from it get them at normal query latency.

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

Common use cases

  • 01 Publish finance rollups computed in Redshift back to spreadsheets or operational tools.
  • 02 Feed customer 360 tables built in Redshift to support and success platforms.
  • 03 Two-way sync between a MySQL application database and a CRM so operational records and sales records stay identical
  • 04 Expose SaaS objects as MySQL tables so legacy internal tools built on MySQL can read live business data

Common sync patterns

Serve warehouse results at database speed

Aggregates or model outputs computed in Amazon Redshift sync into MySQL, 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.

Offload heavy reads

Point analytical queries at the synced copy in Amazon Redshift and keep MySQL focused on its operational workload.

What you can sync between Amazon Redshift and MySQL

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 MySQL objects How this pairing syncs
Tables Columnar tables used as sync destinations for SaaS and database data. Tables The primary sync target; rows map to records in connected systems. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views SQL views readable as modeled sources for reverse syncs. Views Read-side projections used as outbound sync sources. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Stored Procedures SQL procedures sometimes invoked around load steps. Stored Procedures Server-side logic that can post-process synced rows. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Databases Top-level containers within a cluster or serverless workgroup. Databases (Schemas) Top-level namespaces that scope a sync's reads and writes. Databases is specific to Amazon Redshift and Databases (Schemas) to MySQL — each maps to any object or custom field on the other side.
Schemas Namespaces used to organize synced tables and control grants. Columns Field-level mapping targets with engine-typed values. Schemas is specific to Amazon Redshift and Columns to MySQL — each maps to any object or custom field on the other side.
Materialized Views Precomputed results that downstream syncs can read for performance. Primary and Unique Keys Match keys for idempotent upserts and conflict handling. Materialized Views is specific to Amazon Redshift and Primary and Unique Keys to MySQL — each maps to any object or custom field on the other side.

How changes propagate between Amazon Redshift and MySQL

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 MySQL 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 applied to MySQL as a row-level write, with types converted between the two schemas.

MySQL Amazon Redshift Sub-second propagation

DetectionChanges in MySQL are captured at the source via change data capture — no polling loop against its API. Database triggers — Stacksync creates deterministic triggers for internal logging and syncing (requires log_bin_trust_function_creators=ON when.

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.
  • MySQL: No API rate limits; throughput is bounded by connection limits and server resources.
What ships with Amazon Redshift ⇄ MySQL

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Redshift or MySQL 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 MySQL record.

Observability

Monitoring

Track your Amazon Redshift ⇄ MySQL 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 MySQL.

How the Amazon Redshift and MySQL 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

MySQL

Integration surface
SQL wire protocol (MySQL client/server protocol)
Authentication
Database credentials entered as a connection string or parameters, with optional SSL root certificate upload and optional SSH tunnel (SSH user + SSH host)
Change detection
Database triggers — Stacksync creates deterministic triggers for internal logging and syncing (requires log_bin_trust_function_creators=ON when binary logging is enabled)
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by connection limits and server resources
MySQL setup guide
How it works

How to connect Amazon Redshift to MySQL — 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 MySQL 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
    MySQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Amazon Redshift and MySQL 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 582 integrations available for Amazon Redshift and MySQL.

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