Real-time
Two-way sync
Changes in Amazon S3 or InterSystems IRIS instantly reflect in both systems. No stale data, no manual imports.
Storage ⇄ Database
Amazon S3 to InterSystems IRIS integration — real-time, two-way sync
Keep Amazon S3 and InterSystems IRIS in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Amazon S3 and InterSystems IRIS
Keep InterSystems IRIS and Amazon S3 in step: a row in InterSystems IRIS for every file in Amazon S3, with names, paths, metadata, and status staying consistent in real time, in both directions.
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 InterSystems IRIS 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 Tables, Views, Schemas, Persistent Classes in InterSystems IRIS 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.
Common use cases
- 01 Consolidate IRIS data with other databases in an analytics warehouse for cross-system reporting
- 02 Keep reference data consistent between an IRIS-based clinical or financial application and downstream SaaS tools
- 03 Trigger a database or ERP record update the moment an S3 Event Notification fires an object-created event, for example when a partner drops an EDI or invoice file into an inbound prefix.
- 04 Reconcile Object versions and delete markers into an audit table so teams track when files under a compliance prefix were added, replaced, or removed.
Common sync patterns
Continuous archival to file storage
Rows from InterSystems IRIS are written out to Amazon S3 as files on a schedule or as they change, giving a durable, low-cost copy for backup, compliance, or a data lake, without a custom export job to maintain.
A queryable index of the file store
Every file or object in Amazon S3 shows up as a row in InterSystems IRIS, 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.
File metadata kept in step
Tags, custom properties, owner, or status columns edited on a row in InterSystems IRIS 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.
What you can sync between Amazon S3 and InterSystems IRIS
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 | InterSystems IRIS objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Namespaces Namespaces partition databases and determine the connection context for integrations. | Object tags is specific to Amazon S3 and Namespaces to InterSystems IRIS — 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. | Stored Procedures Server-side logic callable over SQL supports controlled writes and transformations. | Object versions is specific to Amazon S3 and Stored Procedures to InterSystems IRIS — each maps to any object or custom field on the other side. | |
| Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. | Tables Relational projections of stored data are the primary read/write surface for SQL-based syncs. | Prefixes (folders) is specific to Amazon S3 and Tables to InterSystems IRIS — each maps to any object or custom field on the other side. | |
| 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. | Views SQL views expose curated slices of data for outbound replication. | Multipart uploads is specific to Amazon S3 and Views to InterSystems IRIS — 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. | Schemas Schema organization scopes which tables a sync connection can see. | Buckets is specific to Amazon S3 and Schemas to InterSystems IRIS — 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. | Persistent Classes Object-model classes project to tables, so class data is reachable through SQL. | Objects is specific to Amazon S3 and Persistent Classes to InterSystems IRIS — each maps to any object or custom field on the other side. |
How changes propagate between Amazon S3 and InterSystems IRIS
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.
Amazon S3 InterSystems IRIS Sub-second propagation
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 InterSystems IRIS as a row-level write, with types converted between the two schemas.
InterSystems IRIS Amazon S3 Interval-based propagation
DetectionStacksync polls InterSystems IRIS for changes on an incremental schedule, reading only records changed since the previous pass. Polling (timestamp or query-based).
DeliveryEach detected change is written to Amazon S3 through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Amazon S3: S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.
- InterSystems IRIS: Constrained by database resources rather than published API rate limits.
What ships with Amazon S3 ⇄ InterSystems IRIS
Connect Amazon S3 and InterSystems IRIS for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–InterSystems IRIS connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon S3 or InterSystems IRIS 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 Amazon S3 or InterSystems IRIS record.
Observability
Monitoring
Track your Amazon S3 ⇄ InterSystems IRIS sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Amazon S3 and InterSystems IRIS.
How the Amazon S3 and InterSystems IRIS connectors work
Amazon S3
- Integration surface
- 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
- Change detection
- 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
- Capabilities
- read · write · webhooks
- Rate limits
- S3 sustains at least 3,500 PUT/COPY/POST/DELETE and 5,500 GET/HEAD requests per second per partitioned prefix and scales higher automatically; bursts can return HTTP 503 SlowDown while it repartitions.
InterSystems IRIS
- Integration surface
- SQL over JDBC/ODBC, plus object and REST access layers
- Authentication
- Database credentials
- Change detection
- Polling (timestamp or query-based); no standard webhook surface
- Capabilities
- read · write
- Rate limits
- Constrained by database resources rather than published API rate limits
How it works
How to connect Amazon S3 to InterSystems IRIS — 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.
- 01
Connect your apps
Authenticate Amazon S3 and InterSystems IRIS with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Amazon S3
connected
InterSystems IRIS
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon S3 and InterSystems IRIS 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.
objects · Amazon S3 ⇄ InterSystems IRISCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Amazon S3 InterSystems IRISCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon S3 and InterSystems IRIS integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Amazon S3 and InterSystems IRIS: authenticate both systems, choose the objects to sync (such as Amazon S3's Object tags and Object versions), map fields visually, and changes propagate both ways in milliseconds — no code required.
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On the InterSystems IRIS side: Tables, Views, Schemas, Persistent Classes, plus custom fields where InterSystems IRIS 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.
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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.
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Common patterns for Amazon S3 and InterSystems IRIS: Continuous archival to file storage; A queryable index of the file store; File metadata kept in step. Rows from InterSystems IRIS are written out to Amazon S3 as files on a schedule or as they change, giving a durable, low-cost copy for backup, compliance, or a data lake, without a custom export job to maintain.
-
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. InterSystems IRIS: SQL over JDBC/ODBC, plus object and REST access layers. Authentication: Database credentials. Stacksync manages authentication, retries, and rate limits on both sides.
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InterSystems IRIS: IRIS is multi-model: the same stored data can be accessed as relational tables via SQL, as persistent objects, and as multidimensional globals, so integrations usually standardize on the SQL projection. Amazon S3: Access is scoped per bucket via IAM and bucket policies; a two-way sync credential needs s3:GetObject, s3:PutObject, s3:ListBucket, and object-tagging permissions. Stacksync's field mapping accounts for these differences between Amazon S3 and InterSystems IRIS without custom code.
SECURITY
Security teams trust 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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 458 integrations available for Amazon S3 and InterSystems IRIS.
Popular · 7 of 458
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Amazon S3 ⇄ IBM Db2 -
Amazon S3 ⇄ Firebase -
Amazon S3 ⇄ SingleStore -
Amazon S3 ⇄ Amazon Aurora -
InterSystems IRIS ⇄ Egnyte -
InterSystems IRIS ⇄ Box -
InterSystems IRIS ⇄ Sharepoint
No integrations match .
