Real-time
Two-way sync
Changes in Azure Cosmos DB or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Database
Azure Cosmos DB to Neo4j integration — real-time, two-way sync
Keep Azure Cosmos DB and Neo4j 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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Migrated from MuleSoft
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Azure Cosmos DB and Neo4j
Keep Azure Cosmos DB and Neo4j 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 Azure Cosmos DB and Neo4j 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 Consolidate documents from multiple containers into a single reporting store.
- 02 Stream operational documents from Cosmos DB into a SQL warehouse via the change feed for analytics without hitting request-unit budgets with full scans.
- 03 Feed identity and access data into a graph for entitlement and blast-radius analysis.
- 04 Write computed relationship scores (fraud, influence, similarity) back to operational systems.
Common sync patterns
Cross-engine sync
Keep the same dataset live in both Azure Cosmos DB and Neo4j, 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 Azure Cosmos DB and Neo4j
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.
| Azure Cosmos DB objects | Neo4j objects | How this pairing syncs | |
|---|---|---|---|
| Databases Top-level namespaces that scope containers and throughput provisioning. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Change feed entries Ordered record of inserts and updates per partition, consumed for incremental sync. | Labels Node type markers used to map source tables or objects onto the graph. | Change feed entries is specific to Azure Cosmos DB and Labels to Neo4j — each maps to any object or custom field on the other side. | |
| Stored procedures and triggers Server-side logic scoped to a partition; relevant when writes must respect existing validation. | Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | Stored procedures and triggers is specific to Azure Cosmos DB and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side. | |
| Containers The unit of partitioning and throughput; each container maps to a synced collection. | Users & Roles Security principals controlling what an integration credential can query or modify. | Containers is specific to Azure Cosmos DB and Users & Roles to Neo4j — each maps to any object or custom field on the other side. | |
| Items (JSON documents) Schema-flexible JSON records read and written during sync; nested structures are flattened or mapped as needed. | Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | Items (JSON documents) is specific to Azure Cosmos DB and Nodes to Neo4j — each maps to any object or custom field on the other side. | |
| Partition keys Determine data distribution and must be included on writes for the sync to route items correctly. | Relationships Typed, directed edges that carry the connections syncs exist to model. | Partition keys is specific to Azure Cosmos DB and Relationships to Neo4j — each maps to any object or custom field on the other side. |
How changes propagate between Azure Cosmos DB and Neo4j
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.
Azure Cosmos DB Neo4j Sub-second propagation
DetectionChanges in Azure Cosmos DB are captured at the source via change data capture — no polling loop against its API. Built-in change feed exposing inserts and updates in order within each partition key range.
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Neo4j Azure Cosmos DB Sub-second propagation
DetectionChanges in Neo4j are captured at the source via change data capture — no polling loop against its API. Neo4j Change Data Capture on Enterprise and Aura streams graph changes.
DeliveryEach detected change is applied to Azure Cosmos DB as a row-level write, with types converted between the two schemas.
What ships with Azure Cosmos DB ⇄ Neo4j
Connect Azure Cosmos DB and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Cosmos DB–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Azure Cosmos DB or Neo4j 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 Azure Cosmos DB or Neo4j record.
Observability
Monitoring
Track your Azure Cosmos DB ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Azure Cosmos DB and Neo4j.
How the Azure Cosmos DB and Neo4j connectors work
Azure Cosmos DB
- Integration surface
- REST API and SDKs over HTTPS (API for NoSQL, formerly the SQL API); also MongoDB, Cassandra, Gremlin, and Table API surfaces
- Authentication
- Account keys, resource tokens, or Microsoft Entra ID role-based access
- Change detection
- Built-in change feed exposing inserts and updates in order within each partition key range
- Capabilities
- read · write · CDC
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
How it works
How to connect Azure Cosmos DB to Neo4j — 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 Azure Cosmos DB and Neo4j with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Azure Cosmos DB
connected
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Azure Cosmos DB and Neo4j 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 · Azure Cosmos DB ⇄ Neo4jCustomers 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.
Azure Cosmos DB Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Azure Cosmos DB and Neo4j integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Azure Cosmos DB and Neo4j: authenticate both systems, choose the objects to sync (such as Azure Cosmos DB's Databases and Change feed entries), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Azure Cosmos DB: The same account can be exposed through multiple wire-compatible APIs (NoSQL, MongoDB, Cassandra, Gremlin, Table), and the API choice fixes how a connector must speak to it. Neo4j: Schema is optional, but uniqueness constraints and indexes are the standard way to make keyed syncs deterministic. Stacksync's field mapping accounts for these differences between Azure Cosmos DB and Neo4j 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 Azure Cosmos DB and Neo4j 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 Azure Cosmos DB and Neo4j connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Cosmos DB–Neo4j integration in-house.
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Yes — Stacksync ships production-grade connectors for both Azure Cosmos DB and Neo4j. 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 Azure Cosmos DB: Built-in change feed exposing inserts and updates in order within each partition key range. On Neo4j: Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 449 integrations available for Azure Cosmos DB and Neo4j.
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