Two-way sync
Changes in Amazon S3 or OpenSearch instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon S3 and OpenSearch 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 OpenSearch 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 Index templates, Ingest pipelines, Data streams, Snapshots in OpenSearch with Buckets, Objects, Object metadata, Object tags 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.
Files that arrive in a folder or bucket in Amazon S3 become rows in OpenSearch as they land, so a database-driven process can pick them up without polling the storage system's API.
Rows from OpenSearch 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.
Every file or object in Amazon S3 shows up as a row in OpenSearch, 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.
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 | OpenSearch 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. | Documents JSON records written via the index and bulk APIs and read via search queries | Object tags is specific to Amazon S3 and Documents to OpenSearch — 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. | Index aliases Stable names over rotating indexes, used for zero-downtime reindex during backfills | Object versions is specific to Amazon S3 and Index aliases to OpenSearch — 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. | Index templates Mapping and settings presets applied to new indexes a sync creates | Prefixes (folders) is specific to Amazon S3 and Index templates to OpenSearch — 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. | Ingest pipelines Server-side processors that transform documents as they are written | Multipart uploads is specific to Amazon S3 and Ingest pipelines to OpenSearch — 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. | Data streams Append-oriented time-series storage for logs and events pushed from source systems | Buckets is specific to Amazon S3 and Data streams to OpenSearch — 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. | Snapshots Backup artifacts, relevant when reseeding an index from a repository | Objects is specific to Amazon S3 and Snapshots to OpenSearch — 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 written to OpenSearch through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls OpenSearch for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.
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–OpenSearch connection.
Changes in Amazon S3 or OpenSearch instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon S3 or OpenSearch 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 OpenSearch record.
Track your Amazon S3 ⇄ OpenSearch sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon S3 and OpenSearch.
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 OpenSearch 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 OpenSearch 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 OpenSearch: 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.
Yes — Stacksync ships production-grade connectors for both Amazon S3 and OpenSearch. 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 OpenSearch: No native change feed; reads rely on queries with scroll or point-in-time polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the OpenSearch side: Index templates, Ingest pipelines, Data streams, Snapshots, plus custom fields where OpenSearch exposes them. On the Amazon S3 side: Buckets, Objects, Object metadata, Object tags. 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 Amazon S3 and OpenSearch: A landing zone for incoming files; Continuous archival to file storage; A queryable index of the file store. Files that arrive in a folder or bucket in Amazon S3 become rows in OpenSearch as they land, so a database-driven process can pick them up without polling the storage system's API.
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 415 integrations available for Amazon S3 and OpenSearch.