Real-time
Two-way sync
Changes in Amazon S3 or Firebase instantly reflect in both systems. No stale data, no manual imports.
Storage ⇄ Database
Amazon S3 to Firebase integration — real-time, two-way sync
Keep Amazon S3 and Firebase in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Amazon S3 and Firebase
Keep Firebase and Amazon S3 in step: a row in Firebase 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 Firebase 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 Realtime Database Nodes, Authentication Users, Cloud Storage Objects, Cloud Functions Triggers in Firebase 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 Mirror Firestore collections into Postgres or a warehouse to run SQL analytics on app data.
- 02 Write CRM-side changes (plan, status, owner) back into Firestore documents the app reads.
- 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
A queryable index of the file store
Every file or object in Amazon S3 shows up as a row in Firebase, 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 Firebase 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 Firebase 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 Firebase
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 | Firebase 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. | Cloud Storage Objects Files referenced from documents; usually synced as metadata plus URLs. | Object tags is specific to Amazon S3 and Cloud Storage Objects to Firebase — 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. | Cloud Functions Triggers Server-side hooks that fire on document changes and can push updates outward. | Object versions is specific to Amazon S3 and Cloud Functions Triggers to Firebase — 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. | Firestore Collections Top-level groupings of documents that a sync maps to tables or SaaS objects. | Prefixes (folders) is specific to Amazon S3 and Firestore Collections to Firebase — 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. | Firestore Documents Schemaless JSON-like records, the primary unit synced to and from external systems. | Multipart uploads is specific to Amazon S3 and Firestore Documents to Firebase — 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. | Subcollections Nested collections under documents, typically flattened into related tables during sync. | Buckets is specific to Amazon S3 and Subcollections to Firebase — 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. | Realtime Database Nodes JSON tree paths in the older Realtime Database, synced by path. | Objects is specific to Amazon S3 and Realtime Database Nodes to Firebase — each maps to any object or custom field on the other side. |
How changes propagate between Amazon S3 and Firebase
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 Firebase 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 written to Firebase through its API, with automatic retries and rate-limit backoff.
Firebase Amazon S3 Interval-based propagation
DetectionStacksync polls Firebase for changes on an incremental schedule, reading only records changed since the previous pass. Real-time snapshot listeners on Firestore queries and Cloud Functions triggers on document changes.
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.
- Firebase: Subject to Firestore's documented operation quotas and per-document write throughput limits.
What ships with Amazon S3 ⇄ Firebase
Connect Amazon S3 and Firebase for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon S3–Firebase connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon S3 or Firebase 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 Firebase record.
Observability
Monitoring
Track your Amazon S3 ⇄ Firebase 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 Firebase.
How the Amazon S3 and Firebase 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.
Firebase
- Integration surface
- REST and gRPC APIs, typically accessed through the Firebase Admin SDK
- Authentication
- Google service account credentials (IAM) for server-side access; Firebase Auth tokens for client contexts
- Change detection
- Real-time snapshot listeners on Firestore queries and Cloud Functions triggers on document changes
- Capabilities
- read · write
- Rate limits
- Subject to Firestore's documented operation quotas and per-document write throughput limits
How it works
How to connect Amazon S3 to Firebase — 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 Firebase 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
Firebase
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon S3 and Firebase 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 ⇄ FirebaseCustomers 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 FirebaseCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon S3 and Firebase integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Amazon S3 and Firebase: 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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Common patterns for Amazon S3 and Firebase: 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 Firebase, 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.
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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. Firebase: REST and gRPC APIs, typically accessed through the Firebase Admin SDK. Authentication: Google service account credentials (IAM) for server-side access; Firebase Auth tokens for client contexts. Stacksync manages authentication, retries, and rate limits on both sides.
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Firebase: Firebase spans two databases with different models: Firestore (collections and documents) and the original Realtime Database (a single JSON tree). Amazon S3: User-defined metadata (x-amz-meta-*) is fixed when an object is written and changing it requires copying the object over itself; only object tags can be updated in place via the tagging API (max 10 tags per object). Stacksync's field mapping accounts for these differences between Amazon S3 and Firebase without custom code.
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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 Firebase records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Amazon S3 and Firebase connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon S3–Firebase integration in-house.
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 523 integrations available for Amazon S3 and Firebase.
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Amazon S3 ⇄ Reltio -
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Firebase ⇄ Egnyte -
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Firebase ⇄ Sharepoint
No integrations match .
