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Data warehouse ⇄ Database

BigQuery to IBM AS/400 integration — real-time, two-way sync

Keep BigQuery 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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  • POC with real engineers in minutes

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Why teams connect BigQuery and IBM AS/400

Connect IBM AS/400 and BigQuery with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want IBM AS/400's rows in BigQuery, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in IBM AS/400 where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in IBM AS/400 sync into BigQuery in real time, and result tables in BigQuery sync back into IBM AS/400, with schema and type mapping between the two systems handled for you.

Common use cases

  • Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • Use journal-based change capture to replicate IBM i data into a cloud warehouse for reporting.
  • Keep customer and item files aligned with an ecommerce platform or modern ERP during phased modernization.

Operational data in the warehouse, minus the pipeline

Rows from IBM AS/400 land in BigQuery as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in BigQuery sync into IBM AS/400, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

What you can sync between BigQuery 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.

BigQuery objects IBM AS/400 objects
Tables The syncable unit: only tables can be synced per the Stacksync docs. Logical files (views) Indexed or filtered views over physical files, usable as read sources.
Partitioned tables Synced like regular tables; partition columns map to target fields. Members Sub-partitions of files in legacy applications, flattened or selected during syncs.
Clustered tables Supported; clustering is transparent to the sync. Rows / records The unit of read and write, accessed via SQL or record-level access.
Datasets Organizational container — you pick which dataset’s tables to sync. Journals and journal receivers The change log that enables log-based CDC on journaled files.
Projects Connection scope: the service account grants access per project. Data queues Program-to-program messaging objects sometimes used to hand events off to integrations.
What ships with BigQuery ⇄ IBM AS/400

Connect BigQuery and IBM AS/400 for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in BigQuery 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 BigQuery 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 BigQuery or IBM AS/400 record.

Observability

Monitoring

Track your BigQuery ⇄ 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 BigQuery and IBM AS/400.

How the BigQuery and IBM AS/400 connectors work

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide

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 BigQuery 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 BigQuery 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
    BigQuery connected
    IBM AS/400 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

BigQuery and IBM AS/400 integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for BigQuery and IBM AS/400.

Popular · 8 of 386
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