Two-way sync
Changes in AWS Aurora MySQL or MySQL instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora MySQL 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.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between AWS Aurora MySQL and MySQL continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Keep the same dataset live in both AWS Aurora MySQL and MySQL, so each workload runs on the engine that suits it.
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.
| AWS Aurora MySQL objects | MySQL objects | |
|---|---|---|
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Databases (Schemas) Top-level namespaces that scope a sync's reads and writes. | |
| Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Tables The primary sync target; rows map to records in connected systems. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | Views Read-side projections used as outbound sync sources. | |
| Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | Columns Field-level mapping targets with engine-typed values. | |
| Views Can serve as read-only sync sources for derived or filtered datasets. | Primary and Unique Keys Match keys for idempotent upserts and conflict handling. | |
| Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | JSON Columns Validated semi-structured payloads for nested SaaS data. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–MySQL connection.
Changes in AWS Aurora MySQL or MySQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora MySQL or 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 AWS Aurora MySQL or MySQL record.
Track your AWS Aurora MySQL ⇄ MySQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and 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 AWS Aurora MySQL 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.
Pick the AWS Aurora MySQL 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.
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 AWS Aurora MySQL and MySQL: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Tables and Rows), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the AWS Aurora MySQL side: Views, Foreign keys, Stored procedures and triggers, Databases (schemas), plus custom fields where AWS Aurora MySQL exposes them. On the MySQL side: JSON Columns, Stored Procedures, Triggers, Databases (Schemas). 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 AWS Aurora MySQL and MySQL: Shared reference data between services; Regional or environment copies; Cross-engine sync. Services that own separate databases stay consistent on the records they share, without a custom replication layer.
AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. MySQL: 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). Stacksync manages authentication, retries, and rate limits on both sides.
AWS Aurora MySQL: Aurora separates compute from a distributed storage layer that replicates data six ways across three Availability Zones, independent of the instances that CDC readers and sync writers connect to. MySQL: The binary log in ROW format records every row-level change, enabling log-based CDC without adding triggers to user tables. Stacksync's field mapping accounts for these differences between AWS Aurora MySQL and 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 AWS Aurora MySQL and MySQL.