Real-time
Two-way sync
Changes in Namely or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Human resources ⇄ Database
Namely to Neo4j integration — real-time, two-way sync
Keep Namely 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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Why teams connect Namely and Neo4j
Put your workforce data where your apps can reach it: Neo4j and Namely share the same people, positions, and org structure in real time.
Namely is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. Neo4j is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Events, Profiles, Job Titles, Job Tiers in Namely need to exist as queryable Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j before an app can act on them. When that bridge is a nightly export or a hand-run CSV, every downstream system spends the day working from a roster that has already moved on.
Stacksync syncs Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j with Events, Profiles, Job Titles, Job Tiers in Namely field by field, in real time. You decide which system owns which fields — Namely typically owns identity and org attributes, while operational or computed values can flow back the other way — and Stacksync keeps every copy consistent, matching records on a stable key and resolving conflicts by rules you set.
The result is one live picture of the workforce on both sides: HR keeps its source of truth, and the database keeps a current mirror that internal apps, reports, and access controls can trust without a batch window in between.
Common use cases
- 01 Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.
- 02 Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
- 03 Push Groups and Teams (departments, locations, team categories) into downstream apps to keep org structure and reporting lines aligned.
- 04 Feed Namely Reports as JSON into a database on a schedule for roster, turnover, and diversity dashboards without manual CSV exports.
Common sync patterns
Mirror people records into the database
Records maintained in Namely land as queryable Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j, so internal apps and dashboards read live data instead of a periodic export.
One directory of record
When a person record is added, changed, or deactivated in either system, the matching row in the other stays current, ending dual maintenance.
Reporting and analytics on current data
Events, Profiles, Job Titles, Job Tiers replicate into Neo4j where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.
What you can sync between Namely 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.
| Namely objects | Neo4j objects | How this pairing syncs | |
|---|---|---|---|
| Groups Departments and locations that organize Profiles; synced to keep org structure aligned with a warehouse or IdP. | Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | Groups is specific to Namely and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side. | |
| Teams Teams and team categories a Profile belongs to; read and written for org-chart and provisioning workflows. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Teams is specific to Namely and Databases to Neo4j — each maps to any object or custom field on the other side. | |
| Reports Saved Namely reports returned as JSON snapshots that update instantly; read-only feeds for headcount and roster analytics. | Users & Roles Security principals controlling what an integration credential can query or modify. | Reports is specific to Namely and Users & Roles to Neo4j — each maps to any object or custom field on the other side. | |
| Profile Fields Metadata describing standard and company-defined custom field sections; read to discover schema and generate mappings. | Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | Profile Fields is specific to Namely and Nodes to Neo4j — each maps to any object or custom field on the other side. | |
| Events Home-feed items such as announcements, birthdays, anniversaries, and new arrivals; typically read-only into comms tools. | Relationships Typed, directed edges that carry the connections syncs exist to model. | Events is specific to Namely and Relationships to Neo4j — each maps to any object or custom field on the other side. | |
| Profiles The core employee record (personal, job, contact, and compensation fields); synced two-way via GET/POST/PUT with updated_at driving incremental polling. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Profiles is specific to Namely and Properties to Neo4j — each maps to any object or custom field on the other side. |
How changes propagate between Namely 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.
Namely Neo4j Interval-based propagation
DetectionStacksync polls Namely for changes on an incremental schedule, reading only records changed since the previous pass. No webhooks.
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Neo4j Namely 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 Namely through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Namely: Namely's public docs do not publish a fixed request quota; the REST API returns standard HTTP status codes, so integrations should throttle and back off on 429/5xx responses.
What ships with Namely ⇄ Neo4j
Connect Namely and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Namely–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Namely 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 Namely or Neo4j record.
Observability
Monitoring
Track your Namely ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Namely and Neo4j.
How the Namely and Neo4j connectors work
Namely
- Integration surface
- REST API (JSON over HTTPS)
- Authentication
- OAuth 2.0 authorization-code grant, or a personal access token sent as a Bearer token; all calls run over HTTPS against https://{subdomain}.namely.com/api/v1
- Change detection
- No webhooks; integrations poll GET endpoints and compare the updated_at / created_at timestamps on Profiles and related objects to detect changes
- Capabilities
- read · write
- Rate limits
- Namely's public docs do not publish a fixed request quota; the REST API returns standard HTTP status codes, so integrations should throttle and back off on 429/5xx responses.
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 Namely 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 Namely 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.
Namely
connected
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Namely 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 · Namely ⇄ 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.
Namely Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Namely and Neo4j integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Namely and Neo4j: authenticate both systems, choose the objects to sync (such as Namely's Groups and Teams), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
On the Neo4j side: Indexes & Constraints, Databases, Users & Roles, Nodes, plus custom fields where Neo4j exposes them. On the Namely side: Events, Profiles, Job Titles, Job Tiers. Stacksync auto-detects both schemas and converts types between the two systems.
-
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.
-
Common patterns for Namely and Neo4j: Mirror people records into the database; One directory of record; Reporting and analytics on current data. Records maintained in Namely land as queryable Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j, so internal apps and dashboards read live data instead of a periodic export.
-
Namely: REST API (JSON over HTTPS). Authentication: OAuth 2.0 authorization-code grant, or a personal access token sent as a Bearer token; all calls run over HTTPS against https://{subdomain}.namely.com/api/v1. Neo4j: Bolt binary protocol with Cypher via official drivers, plus an HTTP query API. Authentication: Username/password (basic auth); enterprise deployments add SSO options. Stacksync manages authentication, retries, and rate limits on both sides.
-
Neo4j: Client drivers connect over the Bolt binary protocol rather than HTTP for query workloads. Namely: Reports return as instantly-updating JSON snapshots; the feed and report surfaces are read-oriented while Profiles, Job Titles, and Groups are read-write. Stacksync's field mapping accounts for these differences between Namely and Neo4j without custom code.
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
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