Two-way sync
Changes in Amazon Redshift or AWS Aurora MySQL instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Redshift and AWS Aurora 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.
Operational databases and analytical warehouses want the same data at different moments. Analysts want AWS Aurora 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 AWS Aurora 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 AWS Aurora MySQL sync into Amazon Redshift in real time, and result tables in Amazon Redshift sync back into AWS Aurora MySQL, with schema and type mapping between the two systems handled for you.
Rows from AWS Aurora MySQL land in Amazon Redshift as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Amazon Redshift sync into AWS Aurora MySQL, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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 | AWS Aurora MySQL objects | |
|---|---|---|
| Stored Procedures SQL procedures sometimes invoked around load steps. | Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | |
| Users and Groups Principals used to grant a sync connection scoped access. | Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | |
| Databases Top-level containers within a cluster or serverless workgroup. | Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | |
| Schemas Namespaces used to organize synced tables and control grants. | Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | |
| Tables Columnar tables used as sync destinations for SaaS and database data. | Columns MySQL data types are mapped to the paired system's field types during schema setup. | |
| Views SQL views readable as modeled sources for reverse syncs. | Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Redshift–AWS Aurora MySQL connection.
Changes in Amazon Redshift or AWS Aurora MySQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Redshift or AWS Aurora MySQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon Redshift or AWS Aurora MySQL record.
Track your Amazon Redshift ⇄ AWS Aurora MySQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Redshift and AWS Aurora MySQL.
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.
Authenticate Amazon Redshift and AWS Aurora MySQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Amazon Redshift and AWS Aurora 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Amazon Redshift and AWS Aurora MySQL: authenticate both systems, choose the objects to sync (such as Amazon Redshift's Stored Procedures and Users and Groups), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Amazon Redshift side: Views, Materialized Views, External Tables (Spectrum), Stored Procedures, plus custom fields where Amazon Redshift exposes them. On the AWS Aurora MySQL side: Databases (schemas), Tables, Rows, Columns. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Amazon Redshift and AWS Aurora MySQL: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from AWS Aurora MySQL land in Amazon Redshift as they change, replacing hand-built CDC and batch extract jobs.
Amazon Redshift: SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS. Authentication: Database credentials or IAM-based authentication. AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
Amazon Redshift: Redshift Spectrum lets queries span external tables on S3, so a sync can read data that never gets loaded into cluster storage. AWS Aurora MySQL: Binlog-based CDC requires binary logging to be enabled through the cluster parameter group; once on, changes can be captured without querying production tables. Stacksync's field mapping accounts for these differences between Amazon Redshift and AWS Aurora MySQL without custom code.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Amazon Redshift and AWS Aurora MySQL.