Real-time
Two-way sync
Changes in MongoDB or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Database
MongoDB to Postgres Heroku integration — real-time, two-way sync
Keep MongoDB and Postgres Heroku 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
Case study
Migrated from MuleSoft
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Migrated from Heroku Connect
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Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect MongoDB and Postgres Heroku
Keep MongoDB and Postgres Heroku synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between MongoDB and Postgres Heroku continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- 01 Replicate operational MongoDB data into a relational database, flattening nested documents into normalized tables for SQL reporting.
- 02 Capture change stream events and propagate them to SaaS tools in near real time instead of running batch exports.
- 03 Keep several Heroku app databases aligned with one system of record
- 04 Reflect billing and subscription records into the app database so product logic reads local rows
Common sync patterns
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
Cross-engine sync
Keep the same dataset live in both MongoDB and Postgres Heroku, so each workload runs on the engine that suits it.
What you can sync between MongoDB and Postgres Heroku
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.
| MongoDB objects | Postgres Heroku objects | How this pairing syncs | |
|---|---|---|---|
| Views Read-only aggregation-defined sources for filtered sync datasets. | Views Read-side projections exposed to outbound syncs. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Collections The table-like sync unit; each collection maps to a table or object in the paired system. | Tables Standard Postgres tables; the primary two-way sync target for app data. | Collections is specific to MongoDB and Tables to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Documents BSON records created, updated, and deleted during syncs, keyed by _id. | Materialized Views Precomputed result sets synced outward on refresh. | Documents is specific to MongoDB and Materialized Views to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. | Schemas Namespaces that scope which tables a sync reads and writes. | Embedded documents and arrays is specific to MongoDB and Schemas to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Indexes Keep lookups by sync key fast on large collections. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | Indexes is specific to MongoDB and Primary and Unique Keys to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Change streams The oplog-backed event feed that powers real-time change capture. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | Change streams is specific to MongoDB and JSONB Columns to Postgres Heroku — each maps to any object or custom field on the other side. |
How changes propagate between MongoDB and Postgres Heroku
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.
MongoDB Postgres Heroku 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 applied to Postgres Heroku as a row-level write, with types converted between the two schemas.
Postgres Heroku MongoDB Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
DeliveryEach detected change is applied to MongoDB as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with MongoDB ⇄ Postgres Heroku
Connect MongoDB and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every MongoDB–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever MongoDB or Postgres Heroku 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 MongoDB or Postgres Heroku record.
Observability
Monitoring
Track your MongoDB ⇄ Postgres Heroku sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between MongoDB and Postgres Heroku.
How the MongoDB and Postgres Heroku connectors work
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
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
How it works
How to connect MongoDB to Postgres Heroku — 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 MongoDB and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
MongoDB
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the MongoDB and Postgres Heroku 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 · MongoDB ⇄ Postgres HerokuCustomers 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.
MongoDB Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
MongoDB and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between MongoDB and Postgres Heroku: authenticate both systems, choose the objects to sync (such as MongoDB's Views and Collections), 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 MongoDB and Postgres Heroku connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom MongoDB–Postgres Heroku integration in-house.
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Yes — Stacksync ships production-grade connectors for both MongoDB and Postgres Heroku. 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 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. On Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. 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: Documents, Embedded documents and arrays, Indexes, Views, plus custom fields where MongoDB exposes them. On the Postgres Heroku side: JSONB Columns, Sequences, Follower Databases, Tables. 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 482 integrations available for MongoDB and Postgres Heroku.
Popular · 6 of 482
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MongoDB ⇄ Google AlloyDB -
MongoDB ⇄ Dynamo DB -
MongoDB ⇄ IBM Db2 -
MongoDB ⇄ Firebase -
Postgres Heroku ⇄ IBM Informix -
Postgres Heroku ⇄ InfluxDB
No integrations match .
