Two-way sync
Changes in AWS Aurora MySQL or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora MySQL and MariaDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Teams sync AWS Aurora MySQL with MariaDB when workloads span a managed AWS database and a self-hosted or differently hosted MariaDB instance. Because both expose Databases (Schemas), Tables, and Views, the sync keeps schema and row data consistent for migrations, replicas, and cross-environment access.
Stacksync syncs tables or collections between AWS Aurora MySQL and MariaDB 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.
Aurora MySQL tables and rows replicate into MariaDB tables to serve reads outside AWS.
Databases (schemas), columns, and primary keys stay aligned while traffic moves between Aurora and MariaDB.
Aurora rows sync into MariaDB System-Versioned Tables so changes are queryable over time.
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 | MariaDB objects | How this pairing syncs | |
|---|---|---|---|
| Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Databases (Schemas) Top-level namespaces that scope a sync's reads and writes. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | 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. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | Columns Field-level mapping targets with engine-typed values. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views Can serve as read-only sync sources for derived or filtered datasets. | 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. | |
| Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | System-Versioned Tables Temporal tables that retain row history natively, useful for auditing synced changes. | Foreign keys is specific to AWS Aurora MySQL and System-Versioned Tables to MariaDB — each maps to any object or custom field on the other side. | |
| Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | JSON Columns Semi-structured payloads validated with JSON functions. | Stored procedures and triggers is specific to AWS Aurora MySQL and JSON Columns to MariaDB — each maps to any object or custom field on the other side. |
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.
DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.
DeliveryEach detected change is applied to MariaDB as a row-level write, with types converted between the two schemas.
DetectionChanges in MariaDB 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.
DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–MariaDB connection.
Changes in AWS Aurora MySQL or MariaDB instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora MySQL or MariaDB 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 MariaDB record.
Track your AWS Aurora MySQL ⇄ MariaDB sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and MariaDB.
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 MariaDB 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 MariaDB 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 MariaDB: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Databases (schemas) and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS Aurora MySQL and MariaDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora MySQL–MariaDB integration in-house.
Yes — Stacksync ships production-grade connectors for both AWS Aurora MySQL and MariaDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on AWS Aurora MySQL: Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback. On MariaDB: Database triggers — Stacksync creates deterministic triggers for internal logging and syncing. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the AWS Aurora MySQL side: Stored procedures and triggers, Databases (schemas), Tables, Rows, plus custom fields where AWS Aurora MySQL exposes them. On the MariaDB side: Databases (Schemas), Tables, Views, 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.
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 387 integrations available for AWS Aurora MySQL and MariaDB.