Real-time
Two-way sync
Changes in Gatekeeper or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Business productivity ⇄ Database
Gatekeeper to Neo4j integration — real-time, two-way sync
Keep Gatekeeper 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.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Gatekeeper and Neo4j
Mirror Gatekeeper's data into Neo4j so your own code can read and write it like any other table, with changes flowing both ways in seconds.
Engineers integrate with tools like Gatekeeper through APIs, which means auth, pagination, rate limits, webhooks, and retry logic, all maintained forever and all different for every tool. Meanwhile the data would be trivial to use if it simply lived in Neo4j.
Stacksync mirrors Workflow form data, Custom data groups, Users, Categories from Gatekeeper into Labels, Indexes & Constraints, Databases, Users & Roles in Neo4j and keeps both sides in sync in real time. Your services query the database directly, and inserts or updates your code makes flow back into Gatekeeper, so the tool and the database never disagree.
Common use cases
- 01 Write contract or vendor records into Gatekeeper when a deal closes in the CRM to kick off downstream procurement and legal workflows.
- 02 Two-way sync Contracts between Gatekeeper and an ERP or warehouse so value, renewal dates, owner, and status stay current without manual re-keying.
- 03 Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.
- 04 Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
Common sync patterns
React to changes as they happen
Updates in Gatekeeper arrive as row changes in Neo4j, so triggers, jobs, and services can respond in near real time.
One integration pattern for the whole stack
Every synced tool looks the same from the database, so each new integration is configuration, not a new codebase.
Read Gatekeeper with a query
Records from Gatekeeper are ordinary rows in Neo4j; join them, index them, and use them in application logic without touching the vendor API.
What you can sync between Gatekeeper 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.
| Gatekeeper objects | Neo4j objects | How this pairing syncs | |
|---|---|---|---|
| Custom data groups Customer-configured custom fields and data groups; because the JSON:API and its docs are dynamic, any custom data added in Configuration exposes the same read/write endpoints as the standard objects and syncs the same way. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Custom data groups is specific to Gatekeeper and Databases to Neo4j — each maps to any object or custom field on the other side. | |
| Users Gatekeeper user and team records governed by role-based access; read to map contract and vendor owners, approvers, and internal contacts to CRM or HR records. | Users & Roles Security principals controlling what an integration credential can query or modify. | Users is specific to Gatekeeper and Users & Roles to Neo4j — each maps to any object or custom field on the other side. | |
| Categories The classification taxonomy applied to contracts and vendors (type, department, business unit); synced so categorization stays consistent between Gatekeeper and downstream reporting or ERP dimensions. | Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | Categories is specific to Gatekeeper and Nodes to Neo4j — each maps to any object or custom field on the other side. | |
| Contracts The core contract records holding value, key dates, renewal terms, status, type, owner, and the linked vendor; created, read, updated, and deleted so contract data moves two-way between Gatekeeper and a database, ERP, or CRM. | Relationships Typed, directed edges that carry the connections syncs exist to model. | Contracts is specific to Gatekeeper and Relationships to Neo4j — each maps to any object or custom field on the other side. | |
| Vendors (Suppliers) Company records for counterparties and suppliers with onboarding status, compliance, risk, contacts, and spend; read and written to keep vendor master data aligned with a CRM or ERP. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Vendors (Suppliers) is specific to Gatekeeper and Properties to Neo4j — each maps to any object or custom field on the other side. | |
| Files Document files attached to contracts and vendors - executed PDFs, certificates, and compliance evidence; read to pull signed files and evidence out, or written to push generated documents in. | Labels Node type markers used to map source tables or objects onto the graph. | Files is specific to Gatekeeper and Labels to Neo4j — each maps to any object or custom field on the other side. |
How changes propagate between Gatekeeper 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.
Gatekeeper Neo4j Interval-based propagation
DetectionStacksync polls Gatekeeper for changes on an incremental schedule, reading only records changed since the previous pass. No native developer webhook subscription API and no database change-data-capture log.
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Neo4j Gatekeeper 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 written to Gatekeeper through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Gatekeeper: Gatekeeper publishes no fixed public per-minute request quota; throughput is governed per key by its endpoint permissions, and every call is recorded (parameters, payload, response) under API Logs for monitoring. Pace bulk writes and use JSON:API pagination on list endpoints.
What ships with Gatekeeper ⇄ Neo4j
Connect Gatekeeper and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Gatekeeper–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Gatekeeper 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 Gatekeeper or Neo4j record.
Observability
Monitoring
Track your Gatekeeper ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Gatekeeper and Neo4j.
How the Gatekeeper and Neo4j connectors work
Gatekeeper
- Integration surface
- RESTful API following the JSON:API specification, tenant-scoped with interactive docs at {tenant}.gatekeeperhq.com/api_docs and a published Postman collection. The API is dynamic: it exposes the standard Contract and Vendor objects plus any custom data groups and workflow-form data configured in the tenant.
- Authentication
- API keys created and managed under Configuration > API Keys and passed as a token; each key carries granular per-endpoint permissions set to read-only or write, so access is scoped per object. Multiple keys can be issued and revoked independently.
- Change detection
- No native developer webhook subscription API and no database change-data-capture log; detect changes by polling the JSON:API list endpoints filtered and sorted on updated-at timestamps. Gatekeeper's own event automation - Workflow Engine phase transitions and Interconnect process orchestration - runs inside the platform rather than as a subscribable webhook stream.
- Capabilities
- read · write
- Rate limits
- Gatekeeper publishes no fixed public per-minute request quota; throughput is governed per key by its endpoint permissions, and every call is recorded (parameters, payload, response) under API Logs for monitoring. Pace bulk writes and use JSON:API pagination on list endpoints.
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 Gatekeeper 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 Gatekeeper 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.
Gatekeeper
connected
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Gatekeeper 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 · Gatekeeper ⇄ 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.
Gatekeeper Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Gatekeeper and Neo4j integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Gatekeeper and Neo4j: authenticate both systems, choose the objects to sync (such as Gatekeeper's Custom data groups and Users), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Gatekeeper: Write access is per API key per endpoint: when you create a key you choose read-only or write for each object, so the API is write-capable and can create and update records rather than only export them. Neo4j: Cypher is its declarative query language, and MERGE semantics give integrations a native upsert primitive for idempotent syncs. Stacksync's field mapping accounts for these differences between Gatekeeper 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 Gatekeeper 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 Gatekeeper and Neo4j connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Gatekeeper–Neo4j integration in-house.
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Yes — Stacksync ships production-grade connectors for both Gatekeeper 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 Gatekeeper: No native developer webhook subscription API and no database change-data-capture log; detect changes by polling the JSON:API list endpoints filtered and sorted on updated-at timestamps. Gatekeeper's own event automation - Workflow Engine phase transitions and Interconnect process orchestration - runs inside the platform rather than as a subscribable webhook stream. 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
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 418 integrations available for Gatekeeper and Neo4j.
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