Real-time
Two-way sync
Changes in Amazon S3 or MongoDB instantly reflect in both systems. No stale data, no manual imports.
Storage ⇄ Database
Amazon S3 to MongoDB integration — real-time, two-way sync
Keep Amazon S3 and MongoDB 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 MongoDB
Keep MongoDB and Amazon S3 in step: a row in MongoDB 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 MongoDB 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 Collections, Documents, Embedded documents and arrays, Indexes in MongoDB with Objects, Object metadata, Object tags, Object versions 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 Sync MongoDB collections with a CRM so customer documents written by the application appear as CRM records, and CRM edits flow back as document updates.
- 02 Replicate operational MongoDB data into a relational database, flattening nested documents into normalized tables for SQL reporting.
- 03 Index every new Object's key, size, LastModified, and user metadata into a Postgres catalog table so applications query S3 contents in SQL instead of paging ListObjectsV2.
- 04 Two-way sync Object tags with a database so retention or classification labels set in an internal app write back onto S3 objects via the tagging API without rewriting the files.
Common sync patterns
A queryable index of the file store
Every file or object in Amazon S3 shows up as a row in MongoDB, 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 MongoDB 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.
Records that point at documents
Where a record in MongoDB 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.
What you can sync between Amazon S3 and MongoDB
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 | MongoDB objects | How this pairing syncs | |
|---|---|---|---|
| Prefixes (folders) Logical path segments in object keys used to scope a sync and to parallelize throughput, since S3 rate limits partition by prefix. | Collections The table-like sync unit; each collection maps to a table or object in the paired system. | Prefixes (folders) is specific to Amazon S3 and Collections to MongoDB — 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. | Documents BSON records created, updated, and deleted during syncs, keyed by _id. | Multipart uploads is specific to Amazon S3 and Documents to MongoDB — 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. | Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. | Buckets is specific to Amazon S3 and Embedded documents and arrays to MongoDB — 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. | Indexes Keep lookups by sync key fast on large collections. | Objects is specific to Amazon S3 and Indexes to MongoDB — 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. | Views Read-only aggregation-defined sources for filtered sync datasets. | Object metadata is specific to Amazon S3 and Views to MongoDB — 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. | Change streams The oplog-backed event feed that powers real-time change capture. | Object tags is specific to Amazon S3 and Change streams to MongoDB — each maps to any object or custom field on the other side. |
How changes propagate between Amazon S3 and MongoDB
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 MongoDB 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 MongoDB as a row-level write, with types converted between the two schemas.
MongoDB Amazon S3 Sub-second propagation
DetectionChanges in MongoDB are captured at the source via change data capture — no polling loop against its API. MongoDB oplog and change streams (requires the database to run as a replica set — even single-node).
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.
What ships with Amazon S3 ⇄ MongoDB
Connect Amazon S3 and MongoDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–MongoDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon S3 or MongoDB 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 MongoDB record.
Observability
Monitoring
Track your Amazon S3 ⇄ MongoDB 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 MongoDB.
How the Amazon S3 and MongoDB 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.
MongoDB
- Integration surface
- MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management
- Authentication
- Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required
- Change detection
- MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time
- Capabilities
- read · write · CDC
How it works
How to connect Amazon S3 to MongoDB — 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 MongoDB 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
MongoDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon S3 and MongoDB 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 ⇄ MongoDBCustomers 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 MongoDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon S3 and MongoDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Amazon S3 and MongoDB: authenticate both systems, choose the objects to sync (such as Amazon S3's Prefixes (folders) and Multipart uploads), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon S3 and MongoDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon S3–MongoDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both Amazon S3 and MongoDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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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 MongoDB: MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the MongoDB side: Collections, Documents, Embedded documents and arrays, Indexes, plus custom fields where MongoDB exposes them. On the Amazon S3 side: Objects, Object metadata, Object tags, Object versions. 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.
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 531 integrations available for Amazon S3 and MongoDB.
Popular · 7 of 531
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Amazon S3 ⇄ Redis Enterprise -
Amazon S3 ⇄ SAP ASE (Sybase) -
Amazon S3 ⇄ Scaleway Postgres -
Amazon S3 ⇄ TiDB -
MongoDB ⇄ Sharepoint -
MongoDB ⇄ Egnyte -
MongoDB ⇄ Box
No integrations match .
