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Data warehouse ⇄ Database

BigQuery to IBM Db2 integration — real-time, two-way sync

Keep BigQuery 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 BigQuery and IBM Db2

Connect IBM Db2 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 Db2'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 Db2 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 Db2 sync into BigQuery in real time, and result tables in BigQuery sync back into IBM Db2, 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
  • Sync SaaS data into Db2 tables that existing enterprise applications and reports already consume.
  • Replicate Db2 tables into a cloud warehouse continuously instead of nightly batch extracts.

Offload heavy reads

Point analytical queries at the synced copy in BigQuery and keep IBM Db2 focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from IBM Db2 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 Db2, where whatever reads from that database gets them without querying the warehouse.

What you can sync between BigQuery 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.

BigQuery objects IBM Db2 objects
Clustered tables Supported; clustering is transparent to the sync. Schemas Namespaces separating synced data from application and system objects.
Datasets Organizational container — you pick which dataset’s tables to sync. Tables Primary read/write target for syncing rows with SaaS systems or other databases.
Projects Connection scope: the service account grants access per project. Views Read-only projections often used to expose curated slices to a sync.
Tables The syncable unit: only tables can be synced per the Stacksync docs. Indexes Support fast key lookups on sync match columns.
Partitioned tables Synced like regular tables; partition columns map to target fields. Stored Procedures Existing business logic sometimes invoked as part of write paths.
What ships with BigQuery ⇄ IBM Db2

Connect BigQuery and IBM Db2 for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery 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 BigQuery or IBM Db2 record.

Observability

Monitoring

Track your BigQuery ⇄ 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 BigQuery and IBM Db2.

How the BigQuery and IBM Db2 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 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 BigQuery 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 BigQuery 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
    BigQuery connected
    IBM Db2 connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the BigQuery 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 · BigQuery ⇄ 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
    BigQuery IBM Db2
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

BigQuery and IBM Db2 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.

Learn more about security
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:

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 386 integrations available for BigQuery and IBM Db2.

Popular · 8 of 386
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