Real-time sync
Changes in IBM AS/400 or Tableau instantly reflect in both systems. No stale data, no manual imports.
Keep IBM AS/400 and Tableau in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Tableau is a read-only source: Stacksync reads its data in real time and delivers it into IBM AS/400, so IBM AS/400 always reflects the current state of Tableau — without exports, scripts, or schedulers.
A database holds the rows your business runs on: the users, events, orders, and records that every service reads and writes. Tableau is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from IBM AS/400 into Tableau usually means a hand-built extract or a change-data-capture pipeline that breaks the moment a column is renamed, and reporting that always trails last night's load.
Attributes teams slice by, such as plan, region, or account owner, stay current in Tableau because they sync from IBM AS/400 as they change, instead of going stale after a one-time import.
Signup, usage, and lifecycle events captured in Tableau sync into IBM AS/400 as rows, so applications and internal tools can read behavioral data next to the records they already keep.
Segments, cohorts, or scores computed in Tableau sync back into IBM AS/400, where the services that read from the database act on them at query speed without calling the analytics API.
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.
| IBM AS/400 objects | Tableau objects | How this pairing syncs | |
|---|---|---|---|
| Rows / records The unit of read and write, accessed via SQL or record-level access. | Projects Folders that organize content and set permissions; listed via REST to mirror the site's content hierarchy into a catalog. | Rows / records is specific to IBM AS/400 and Projects to Tableau — each maps to any object or custom field on the other side. | |
| Journals and journal receivers The change log that enables log-based CDC on journaled files. | Users Site users with site roles and group membership; read via REST for access reviews and to reconcile identities against an HR or IdP source. | Journals and journal receivers is specific to IBM AS/400 and Users to Tableau — each maps to any object or custom field on the other side. | |
| Data queues Program-to-program messaging objects sometimes used to hand events off to integrations. | Databases and Tables External assets indexed by Tableau Catalog; queried via the Metadata API GraphQL endpoint for lineage and impact analysis. | Data queues is specific to IBM AS/400 and Databases and Tables to Tableau — each maps to any object or custom field on the other side. | |
| Libraries The schema-equivalent containers that scope which files a sync reads. | Extract Refresh Tasks Scheduled extract refreshes; status and history read via REST, with DatasourceRefreshSucceeded and Failed events delivered by webhooks. | Libraries is specific to IBM AS/400 and Extract Refresh Tasks to Tableau — each maps to any object or custom field on the other side. | |
| Physical files (tables) The Db2 for i tables mapped directly to sync targets. | Fields and Columns Columns and calculated fields with their descriptions, exposed by the Metadata API; read to populate a data catalog with governed definitions. | Physical files (tables) is specific to IBM AS/400 and Fields and Columns to Tableau — each maps to any object or custom field on the other side. | |
| Logical files (views) Indexed or filtered views over physical files, usable as read sources. | Published Data Sources Published data sources (.tdsx); their underlying rows are read via the VizQL Data Service, and refresh state is tracked through content webhooks. | Logical files (views) is specific to IBM AS/400 and Published Data Sources to Tableau — 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 IBM AS/400 are captured at the source via change data capture — no polling loop against its API. Journal-based CDC by reading journal receivers on journaled files.
DeliveryTableau does not accept inbound record writes, so this direction carries requests rather than records: Tableau's output flows back as field updates on the originating IBM AS/400 records.
DetectionTableau notifies Stacksync of record changes through webhook events. Webhooks fire on workbook and data source create/update/delete and extract refresh events.
DeliveryEach detected change is applied to IBM AS/400 as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every IBM AS/400–Tableau connection.
Changes in IBM AS/400 or Tableau instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever IBM AS/400 or Tableau data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single IBM AS/400 or Tableau record.
Track your IBM AS/400 ⇄ Tableau sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between IBM AS/400 and Tableau.
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 IBM AS/400 and Tableau 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 IBM AS/400 and Tableau 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 integration between IBM AS/400 and Tableau — Tableau is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both IBM AS/400 and Tableau. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on IBM AS/400: Journal-based CDC by reading journal receivers on journaled files; polling as a fallback. On Tableau: Webhooks fire on workbook and data source create/update/delete and extract refresh events; otherwise content and metadata are polled via REST list endpoints (updatedAt) and the Metadata API. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Tableau side: Databases and Tables, Extract Refresh Tasks, Fields and Columns, Published Data Sources, plus custom fields where Tableau exposes them. On the IBM AS/400 side: Journals and journal receivers, Data queues, Libraries, Physical files (tables). Stacksync auto-detects both schemas and converts types between the two systems.
Tableau is a read-only source, so this integration runs one-way: Stacksync reads from Tableau in real time and delivers into IBM AS/400. Field mapping and monitoring work the same as for two-way pairs.
Common patterns for IBM AS/400 and Tableau: Filter and grouping dimensions kept fresh; Where Tableau tracks product events: behavior onto stored records; Where Tableau builds cohorts or scores: results your services can read. Attributes teams slice by, such as plan, region, or account owner, stay current in Tableau because they sync from IBM AS/400 as they change, instead of going stale after a one-time import.
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.
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Every pair below is a real-time, two-way sync. Search all 365 integrations available for IBM AS/400 and Tableau.