Two-way sync
Changes in Amazon S3 or IBM Informix instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 and IBM Informix 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 Informix 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 Views, TimeSeries objects, Stored procedures, Logical logs in IBM Informix 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 Informix, 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 Informix 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 Informix 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 Informix 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. | Logical logs The transaction log that Informix's CDC interface reads committed changes from. | Multipart uploads is specific to Amazon S3 and Logical logs to IBM Informix — 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. | Databases Top-level containers that scope a sync connection. | Buckets is specific to Amazon S3 and Databases to IBM Informix — 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. | Tables Relational tables mapped directly to sync targets. | Objects is specific to Amazon S3 and Tables to IBM Informix — 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. | Rows The unit of read and write, keyed by primary key. | Object metadata is specific to Amazon S3 and Rows to IBM Informix — 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. | Views Read-only projections used to shape outbound data. | Object tags is specific to Amazon S3 and Views to IBM Informix — 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. | TimeSeries objects Informix's native time-series type, usually exposed to syncs through virtual tables. | Object versions is specific to Amazon S3 and TimeSeries objects to IBM Informix — 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 Informix as a row-level write, with types converted between the two schemas.
DetectionChanges in IBM Informix are captured at the source via change data capture — no polling loop against its API. Informix's Change Data Capture API reading committed changes from logical logs.
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 Informix connection.
Changes in Amazon S3 or IBM Informix instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 or IBM Informix 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 Informix record.
Track your Amazon S3 ⇄ IBM Informix sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 and IBM Informix.
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 Informix 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 Informix 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 Informix: 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.
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 Amazon S3 and IBM Informix: A queryable index of the file store; File metadata kept in step; Records that point at documents. Every file or object in Amazon S3 shows up as a row in IBM Informix, 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.
Amazon S3: S3 REST API (also via AWS SDKs and the S3-compatible endpoint). Authentication: AWS IAM credentials — an access key ID and secret access key signed with AWS Signature Version 4; supports temporary STS credentials and cross-account IAM roles. IBM Informix: SQL over JDBC/ODBC drivers; DRDA connectivity is also supported. Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
IBM Informix: Informix ships a Change Data Capture API that streams committed row changes from its logical logs, so log-based replication does not require triggers. Amazon S3: S3 provides strong read-after-write consistency for all operations, but it has no built-in change feed — near-real-time detection depends on S3 Event Notifications or EventBridge being configured on the bucket. Stacksync's field mapping accounts for these differences between Amazon S3 and IBM Informix without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Amazon S3 and IBM Informix records are not retained after a sync operation.
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 447 integrations available for Amazon S3 and IBM Informix.