Two-way sync
Changes in Amazon S3 or IBM AS/400 instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 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.
A database holds structured records; a storage system holds the files those records depend on, such as contracts, images, exports, uploads, and documents. The two describe the same things from opposite sides: a row in IBM AS/400 says a file exists and carries its name, location, and status, while Amazon S3 holds the bytes. Linked only by a hand-kept path or a one-off script, the two drift the moment a file is renamed, moved, or deleted and the record still points at where it used to be.
Stacksync syncs Data queues, Libraries, Physical files (tables), Logical files (views) in IBM AS/400 with Multipart uploads, Buckets, Objects, Object metadata in Amazon S3 bi-directionally and in real time. File attributes, including name, path or object key, size, type, modified time, owner, and tags or custom properties, map field by field to columns on the matching row, and a change on either side shows up on the other within seconds. New files appear as rows, metadata edits travel in the direction you choose, and deletes stay consistent, with conflict rules you set in place of nightly reconciliation scripts.
Every file or object in Amazon S3 shows up as a row in IBM AS/400, with its name, folder or key, size, type, and modified date as columns, so the contents of the store can be listed, filtered, and joined like any other table.
Tags, custom properties, owner, or status columns edited on a row in IBM AS/400 write back to the matching file's metadata in Amazon S3, and metadata changed in Amazon S3 updates the row, so the two never disagree about a file.
Where a record in IBM AS/400 references a file in Amazon S3, such as a contract, an image, an export, or an upload, the reference, path, and status stay consistent as files are renamed, moved, or replaced, so stored links keep resolving.
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.
| Amazon S3 objects | IBM AS/400 objects | How this pairing syncs | |
|---|---|---|---|
| Multipart uploads In-progress large-object uploads assembled from parts; objects above ~100 MB (required above 5 GB) are written this way, and incomplete uploads persist until completed or aborted. | Members Sub-partitions of files in legacy applications, flattened or selected during syncs. | Multipart uploads is specific to Amazon S3 and Members to IBM AS/400 — each maps to any object or custom field on the other side. | |
| Buckets Top-level, region-scoped containers that hold objects; enumerated to discover the namespaces and prefixes a sync should cover. | Rows / records The unit of read and write, accessed via SQL or record-level access. | Buckets is specific to Amazon S3 and Rows / records to IBM AS/400 — each maps to any object or custom field on the other side. | |
| Objects Files stored under a key; content is read with GET and written with PUT, and each object's key/size/ETag/LastModified is the unit indexed into a database. | Journals and journal receivers The change log that enables log-based CDC on journaled files. | Objects is specific to Amazon S3 and Journals and journal receivers to IBM AS/400 — each maps to any object or custom field on the other side. | |
| Object metadata System metadata (Content-Type, size, ETag, LastModified) plus user-defined x-amz-meta-* headers; user metadata is fixed at write time and only changeable by rewriting the object. | Data queues Program-to-program messaging objects sometimes used to hand events off to integrations. | Object metadata is specific to Amazon S3 and Data queues to IBM AS/400 — each maps to any object or custom field on the other side. | |
| Object tags Up to 10 key-value tags per object, mutable in place via the tagging API independent of content, so classification and retention labels sync two-way without rewriting files. | Libraries The schema-equivalent containers that scope which files a sync reads. | Object tags is specific to Amazon S3 and Libraries to IBM AS/400 — each maps to any object or custom field on the other side. | |
| Object versions When bucket versioning is enabled every write creates a new version ID; prior versions and delete markers are readable for history and audit syncs. | Physical files (tables) The Db2 for i tables mapped directly to sync targets. | Object versions is specific to Amazon S3 and Physical files (tables) to IBM AS/400 — 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.
DetectionAmazon S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge.
DeliveryEach detected change is applied to IBM AS/400 as a row-level write, with types converted between the two schemas.
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.
DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–IBM AS/400 connection.
Changes in Amazon S3 or IBM AS/400 instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 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 Amazon S3 or IBM AS/400 record.
Track your Amazon S3 ⇄ IBM AS/400 sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 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 Amazon S3 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 Amazon S3 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 Amazon S3 and IBM AS/400: authenticate both systems, choose the objects to sync (such as Amazon S3's Multipart uploads and Buckets), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon S3 and IBM AS/400 connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon S3–IBM AS/400 integration in-house.
Yes — Stacksync ships production-grade connectors for both Amazon S3 and IBM AS/400. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Amazon S3: S3 Event Notifications push object-created, object-removed, and object-tagging events to SNS, SQS, Lambda, or EventBridge; there is no modified-since query, so polling relies on each object's LastModified from ListObjectsV2. On IBM AS/400: Journal-based CDC by reading journal receivers on journaled files; polling as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the IBM AS/400 side: Data queues, Libraries, Physical files (tables), Logical files (views), plus custom fields where IBM AS/400 exposes them. On the Amazon S3 side: Multipart uploads, Buckets, Objects, Object metadata. 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.
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 424 integrations available for Amazon S3 and IBM AS/400.