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AWS Aurora MySQL to IBM AS/400 integration — real-time, two-way sync

Keep AWS Aurora MySQL and IBM AS/400 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 AWS Aurora MySQL and IBM AS/400

Keep AWS Aurora MySQL and IBM AS/400 synchronized in real time, across engines, regions, or services, in one or both directions.

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 IBM AS/400 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.

Common use cases

  • 01 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
  • 02 Let operations teams edit records in a spreadsheet-style tool with changes written back to Aurora safely.
  • 03 Use journal-based change capture to replicate IBM i data into a cloud warehouse for reporting.
  • 04 Keep customer and item files aligned with an ecommerce platform or modern ERP during phased modernization.

Common sync patterns

Cross-engine sync

Keep the same dataset live in both AWS Aurora MySQL and IBM AS/400, so each workload runs on the engine that suits it.

Migration with zero-downtime cutover

When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

What you can sync between AWS Aurora MySQL and IBM AS/400

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 IBM AS/400 objects How this pairing syncs
Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. Data queues Program-to-program messaging objects sometimes used to hand events off to integrations. Foreign keys is specific to AWS Aurora MySQL and Data queues to IBM AS/400 — 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. Libraries The schema-equivalent containers that scope which files a sync reads. Stored procedures and triggers is specific to AWS Aurora MySQL and Libraries to IBM AS/400 — each maps to any object or custom field on the other side.
Databases (schemas) Logical namespaces that scope which tables a sync connection can see. Physical files (tables) The Db2 for i tables mapped directly to sync targets. Databases (schemas) is specific to AWS Aurora MySQL and Physical files (tables) to IBM AS/400 — each maps to any object or custom field on the other side.
Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. Logical files (views) Indexed or filtered views over physical files, usable as read sources. Tables is specific to AWS Aurora MySQL and Logical files (views) to IBM AS/400 — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. Members Sub-partitions of files in legacy applications, flattened or selected during syncs. Rows is specific to AWS Aurora MySQL and Members to IBM AS/400 — each maps to any object or custom field on the other side.
Columns MySQL data types are mapped to the paired system's field types during schema setup. Rows / records The unit of read and write, accessed via SQL or record-level access. Columns is specific to AWS Aurora MySQL and Rows / records to IBM AS/400 — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora MySQL and IBM AS/400

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.

AWS Aurora MySQL IBM AS/400 Sub-second propagation

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 IBM AS/400 as a row-level write, with types converted between the two schemas.

IBM AS/400 AWS Aurora MySQL Sub-second propagation

DetectionChanges in IBM AS/400 are captured at the source via change data capture — no polling loop against its API. Journal-based CDC by reading journal receivers on journaled files.

DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • IBM AS/400: Bounded by system resources and subsystem configuration rather than an API quota.
What ships with AWS Aurora MySQL ⇄ IBM AS/400

Connect AWS Aurora MySQL and IBM AS/400 for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–IBM AS/400 connection.

Real-time

Two-way sync

Changes in AWS Aurora MySQL or IBM AS/400 instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora MySQL or IBM AS/400 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 AWS Aurora MySQL or IBM AS/400 record.

Observability

Monitoring

Track your AWS Aurora MySQL ⇄ IBM AS/400 sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and IBM AS/400.

How the AWS Aurora MySQL and IBM AS/400 connectors work

AWS Aurora MySQL

Integration surface
SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback
Capabilities
read · write · CDC

IBM AS/400

Integration surface
SQL over JDBC/ODBC to Db2 for i (for example the JTOpen/jt400 driver), alongside native record-level access
Authentication
IBM i user profile credentials (database credentials)
Change detection
Journal-based CDC by reading journal receivers on journaled files; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Bounded by system resources and subsystem configuration rather than an API quota.
How it works

How to connect AWS Aurora MySQL to IBM AS/400 — 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 AWS Aurora MySQL and IBM AS/400 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
    AWS Aurora MySQL connected
    IBM AS/400 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora MySQL and IBM AS/400 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 · AWS Aurora MySQL ⇄ IBM AS/400
    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
    AWS Aurora MySQL IBM AS/400
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora MySQL and IBM AS/400 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 379 integrations available for AWS Aurora MySQL and IBM AS/400.

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