Real-time
Two-way sync
Changes in Neo4j or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Database
Neo4j to PostgreSQL integration — real-time, two-way sync
Keep Neo4j and PostgreSQL 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
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Neo4j and PostgreSQL
Keep Neo4j and PostgreSQL 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 Neo4j and PostgreSQL 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
- Sync product catalog and order history into Neo4j to power recommendation queries.
- Feed identity and access data into a graph for entitlement and blast-radius analysis.
- Let an application write to its own database and have those rows appear as records in business systems in near real time
- Consolidate data from several microservice databases into one operational Postgres store
Cross-engine sync
Keep the same dataset live in both Neo4j and PostgreSQL, so each workload runs on the engine that suits it.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
What you can sync between Neo4j and PostgreSQL
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.
| Neo4j objects | PostgreSQL objects | |
|---|---|---|
| Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. | |
| Users & Roles Security principals controlling what an integration credential can query or modify. | Sequences Generate surrogate keys for rows created by inbound syncs. | |
| Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. | |
| Relationships Typed, directed edges that carry the connections syncs exist to model. | Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. | |
| Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Views Read-side projections used to expose joined or filtered data to a sync. | |
| Labels Node type markers used to map source tables or objects onto the graph. | Materialized Views Precomputed result sets synced outward on a refresh schedule. |
What ships with Neo4j ⇄ PostgreSQL
Connect Neo4j and PostgreSQL for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Neo4j–PostgreSQL connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Neo4j or PostgreSQL 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 Neo4j or PostgreSQL record.
Observability
Monitoring
Track your Neo4j ⇄ PostgreSQL sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Neo4j and PostgreSQL.
How the Neo4j and PostgreSQL connectors work
Neo4j
- Integration surface
- Bolt binary protocol with Cypher via official drivers, plus an HTTP query API
- Authentication
- Username/password (basic auth); enterprise deployments add SSO options
- Change detection
- Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties
- Capabilities
- read · write · CDC
PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL frontend/backend protocol)
- Authentication
- Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
- Change detection
- Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
How it works
How to connect Neo4j to PostgreSQL — 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 Neo4j and PostgreSQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Neo4j
connected
PostgreSQL
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Neo4j and PostgreSQL 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 · Neo4j ⇄ PostgreSQLCustomers 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.
Neo4j PostgreSQLCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Neo4j and PostgreSQL integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Neo4j and PostgreSQL: authenticate both systems, choose the objects to sync (such as Neo4j's Databases and Users & Roles), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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 Neo4j and PostgreSQL: Cross-engine sync; Migration with zero-downtime cutover; Shared reference data between services. Keep the same dataset live in both Neo4j and PostgreSQL, so each workload runs on the engine that suits it.
-
Neo4j: Bolt binary protocol with Cypher via official drivers, plus an HTTP query API. Authentication: Username/password (basic auth); enterprise deployments add SSO options. PostgreSQL: SQL wire protocol (PostgreSQL frontend/backend protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user. Stacksync manages authentication, retries, and rate limits on both sides.
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Neo4j: Neo4j uses a property graph model in which nodes and relationships both carry key-value properties, so edges hold data rather than just linking rows. PostgreSQL: Logical decoding of the write-ahead log (wal_level=logical) provides row-level change capture without adding triggers to user tables. Stacksync's field mapping accounts for these differences between Neo4j and PostgreSQL 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 Neo4j and PostgreSQL records are not retained after a sync operation.
SECURITY
Security teams love 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
CSA STAR
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 386 integrations available for Neo4j and PostgreSQL.
Popular · 8 of 386
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Neo4j ⇄ Dynamo DB -
Neo4j ⇄ IBM Db2 -
Neo4j ⇄ Firebase -
Neo4j ⇄ SingleStore -
PostgreSQL ⇄ Elasticsearch -
PostgreSQL ⇄ Google Cloud Spanner - PostgreSQL ⇄ Google Cloud SQL
- PostgreSQL ⇄ IBM AS/400
No integrations match .
