Two-way sync
Changes in BigQuery or IBM AS/400 instantly reflect in both systems. No stale data, no manual imports.
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.
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.
Rows from IBM AS/400 land in BigQuery as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in BigQuery sync into IBM AS/400, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–IBM AS/400 connection.
Changes in BigQuery or IBM AS/400 instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever BigQuery or IBM AS/400 data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single BigQuery or IBM AS/400 record.
Track your BigQuery ⇄ IBM AS/400 sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between BigQuery and IBM AS/400.
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 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.
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.
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 two-way integration between BigQuery and IBM AS/400: authenticate both systems, choose the objects to sync (such as BigQuery's Tables and Partitioned tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the BigQuery side: Clustered tables, Datasets, Projects, Tables, plus custom fields where BigQuery exposes them. On the IBM AS/400 side: Logical files (views), Members, Rows / records, Journals and journal receivers. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for BigQuery and IBM AS/400: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from IBM AS/400 land in BigQuery as they change, replacing hand-built CDC and batch extract jobs.
BigQuery: 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. IBM AS/400: 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). Stacksync manages authentication, retries, and rate limits on both sides.
BigQuery: Google quota of 1,500 table modifications per BigQuery table per day (DELETE, INSERT, MERGE, TRUNCATE TABLE, UPDATE). IBM AS/400: Standard access is SQL over JDBC/ODBC (commonly the open-source JTOpen driver), coexisting with legacy record-level access. Stacksync's field mapping accounts for these differences between BigQuery and IBM AS/400 without custom code.
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.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for BigQuery and IBM AS/400.