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AWS Aurora PostgreSQL to IBM Db2 integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL 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.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect AWS Aurora PostgreSQL and IBM Db2

Keep AWS Aurora PostgreSQL and IBM Db2 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 PostgreSQL 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.

Common use cases

  • 01 Feed operational dashboards from a read replica while the writer handles sync traffic.
  • 02 Expose ERP records such as customers, orders, and invoices as Postgres tables the engineering team can query and update with plain SQL.
  • 03 Feed changes captured from Db2 logs into downstream event pipelines.
  • 04 Expose Db2 records that back core business systems to a CRM so sales and support see order or account state.

Common sync patterns

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.

Regional or environment copies

Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.

What you can sync between AWS Aurora PostgreSQL and IBM Db2

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 PostgreSQL objects IBM Db2 objects How this pairing syncs
Tables The core sync unit; rows are matched across systems by primary key. 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.
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. Databases The connection target; each database holds the schemas a sync addresses. Databases and schemas is specific to AWS Aurora PostgreSQL and Databases to IBM Db2 — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. Schemas Namespaces separating synced data from application and system objects. Rows is specific to AWS Aurora PostgreSQL and Schemas to IBM Db2 — each maps to any object or custom field on the other side.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. Views Read-only projections often used to expose curated slices to a sync. Columns is specific to AWS Aurora PostgreSQL and Views to IBM Db2 — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Indexes Support fast key lookups on sync match columns. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Indexes to IBM Db2 — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Stored Procedures Existing business logic sometimes invoked as part of write paths. Views and materialized views is specific to AWS Aurora PostgreSQL and Stored Procedures to IBM Db2 — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL and IBM Db2

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 PostgreSQL IBM Db2 Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

DeliveryEach detected change is applied to IBM Db2 as a row-level write, with types converted between the two schemas.

IBM Db2 AWS Aurora PostgreSQL Sub-second propagation

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 PostgreSQL as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • IBM Db2: No API rate limits; throughput is bounded by instance resources and workload management settings.
What ships with AWS Aurora PostgreSQL ⇄ IBM Db2

Connect AWS Aurora PostgreSQL and IBM Db2 for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–IBM Db2 connection.

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL or IBM Db2 instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL or IBM Db2 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 PostgreSQL or IBM Db2 record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ IBM Db2 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 PostgreSQL and IBM Db2.

How the AWS Aurora PostgreSQL and IBM Db2 connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC

IBM Db2

Integration surface
SQL via JDBC/ODBC/CLI drivers; optional REST endpoints in some editions
Authentication
Database credentials, typically backed by OS or LDAP authentication
Change detection
Log-based CDC through IBM's replication tooling where licensed; otherwise polling on timestamp or audit columns
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by instance resources and workload management settings
How it works

How to connect AWS Aurora PostgreSQL to IBM Db2 — 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 PostgreSQL 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    AWS Aurora PostgreSQL connected
    IBM Db2 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · AWS Aurora PostgreSQL ⇄ IBM Db2
    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 PostgreSQL IBM Db2
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

AWS Aurora PostgreSQL and IBM Db2 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.

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:

Related integrations

Every pair below is a real-time, two-way sync. Search all 398 integrations available for AWS Aurora PostgreSQL and IBM Db2.

Popular · 4 of 398
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