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Data warehouse ⇄ Database

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

Keep Databricks 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.

  • 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 Databricks and IBM AS/400

Connect IBM AS/400 and Databricks 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 Databricks, 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 Databricks in real time, and result tables in Databricks sync back into IBM AS/400, with schema and type mapping between the two systems handled for you.

Common use cases

  • Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 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.

Offload heavy reads

Point analytical queries at the synced copy in Databricks and keep IBM AS/400 focused on its operational workload.

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

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

What you can sync between Databricks 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.

Databricks objects IBM AS/400 objects
Volumes Unity Catalog file storage used for staging bulk loads. Rows / records The unit of read and write, accessed via SQL or record-level access.
SQL Warehouses The compute endpoint a sync connects to for query execution. Journals and journal receivers The change log that enables log-based CDC on journaled files.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Data queues Program-to-program messaging objects sometimes used to hand events off to integrations.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Libraries The schema-equivalent containers that scope which files a sync reads.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Physical files (tables) The Db2 for i tables mapped directly to sync targets.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Logical files (views) Indexed or filtered views over physical files, usable as read sources.
What ships with Databricks ⇄ IBM AS/400

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

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

Real-time

Two-way sync

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

Observability

Monitoring

Track your Databricks ⇄ 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 Databricks and IBM AS/400.

How the Databricks and IBM AS/400 connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

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

    Choose tables

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

Databricks 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.

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 Databricks and IBM AS/400.

Popular · 8 of 386
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