Two-way sync
Changes in AWS Aurora MySQL or IBM Db2 instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora MySQL and IBM Db2 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 IBM Db2 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.
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 IBM Db2, so each workload runs on the engine that suits it.
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
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 Db2 objects | How this pairing syncs | |
|---|---|---|---|
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Tables Primary read/write target for syncing rows with SaaS systems or other databases. | 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-only projections often used to expose curated slices to a sync. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Stored Procedures Existing business logic sometimes invoked as part of write paths. | Rows is specific to AWS Aurora MySQL and Stored Procedures to IBM Db2 — 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. | Sequences ID generation relevant when external systems insert rows. | Columns is specific to AWS Aurora MySQL and Sequences to IBM Db2 — each maps to any object or custom field on the other side. | |
| Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | Tablespaces Physical storage layout that operators consider when adding synced tables. | Primary keys and indexes is specific to AWS Aurora MySQL and Tablespaces to IBM Db2 — each maps to any object or custom field on the other side. | |
| Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | Databases The connection target; each database holds the schemas a sync addresses. | Foreign keys is specific to AWS Aurora MySQL and Databases to IBM Db2 — 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 IBM Db2 as a row-level write, with types converted between the two schemas.
DetectionChanges in IBM Db2 are captured at the source via change data capture — no polling loop against its API. Log-based CDC through IBM's replication tooling where licensed.
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–IBM Db2 connection.
Changes in AWS Aurora MySQL or IBM Db2 instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora MySQL or IBM Db2 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 IBM Db2 record.
Track your AWS Aurora MySQL ⇄ IBM Db2 sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and IBM Db2.
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 IBM Db2 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 IBM Db2 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 IBM Db2: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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 IBM Db2: Regional or environment copies; Cross-engine sync; Migration with zero-downtime cutover. Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. IBM Db2: SQL via JDBC/ODBC/CLI drivers; optional REST endpoints in some editions. Authentication: Database credentials, typically backed by OS or LDAP authentication. Stacksync manages authentication, retries, and rate limits on both sides.
AWS Aurora MySQL: Read replicas share the cluster storage volume, letting syncs read from a replica endpoint without adding load to the writer. IBM Db2: Db2 ships in distinct variants (LUW, z/OS, IBM i) whose SQL dialects and catalog views differ, so integrations must target the right edition. Stacksync's field mapping accounts for these differences between AWS Aurora MySQL and IBM Db2 without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means AWS Aurora MySQL and IBM Db2 records are not retained after a sync operation.
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 396 integrations available for AWS Aurora MySQL and IBM Db2.