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Human resources ⇄ Database

Lever to Neo4j integration — real-time, two-way sync

Keep Lever 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 Lever and Neo4j

Put your workforce data where your apps can reach it: Neo4j and Lever share the same people, positions, and org structure in real time.

Lever 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: Interviews, Notes and Contacts, Opportunities, Postings in Lever need to exist as queryable Users & Roles, Nodes, Relationships, Properties 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 Users & Roles, Nodes, Relationships, Properties in Neo4j with Interviews, Notes and Contacts, Opportunities, Postings in Lever field by field, in real time. You decide which system owns which fields — Lever 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 Sync product catalog and order history into Neo4j to power recommendation queries.
  • 02 Feed identity and access data into a graph for entitlement and blast-radius analysis.
  • 03 Consolidate Feedback, Interviews, and Notes into a warehouse for interviewer scorecard and time-to-fill reporting.
  • 04 Write enriched Sources, Tags, and Contact data back onto Opportunities from an outbound sourcing pipeline.

Common sync patterns

Reporting and analytics on current data

Interviews, Notes and Contacts, Opportunities, Postings replicate into Neo4j where they join operational tables, so headcount, roles, and status reports run on the live state without manual pulls.

Org and structure stay aligned

Groups, departments, managers, and reporting lines from Lever stay consistent in Neo4j, so hierarchy-driven logic and permissions don't drift.

Computed and operational fields flow back

Values assembled or corrected in Neo4j write onto the matching record in Lever where those fields are writable, keeping the people system enriched.

What you can sync between Lever 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.

Lever objects Neo4j objects How this pairing syncs
Notes and Contacts Free-text Notes on Opportunities plus the underlying Contact (person) that dedupes multiple Opportunities; notes are posted via POST /opportunities/:id/notes and contact-level tags, sources, and links can be added back for attribution. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Notes and Contacts is specific to Lever and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side.
Opportunities The core pipeline record for a candidate applying to a role; replaced the deprecated Candidates endpoint. Created via POST /opportunities and updated (stage, archive, links, tags, sources, files) through the API, and synced two-way with a database or HRIS. Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Opportunities is specific to Lever and Databases to Neo4j — each maps to any object or custom field on the other side.
Postings Job posting records with categories, apply URLs, workplace type, and requisition codes. Can be created via POST /postings and read into a warehouse for open-role reporting. Users & Roles Security principals controlling what an integration credential can query or modify. Postings is specific to Lever and Users & Roles to Neo4j — each maps to any object or custom field on the other side.
Requisitions Headcount/requisition records with custom requisition fields, tied to Postings; read via GET /requisitions and synced to an HRIS to reconcile approved headcount against open roles. Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Requisitions is specific to Lever and Nodes to Neo4j — each maps to any object or custom field on the other side.
Offers Offer records attached to an Opportunity with status and offer-form fields; exposed read-only through GET /opportunities/:id/offers, so they sync outbound to an HRIS or onboarding system when a candidate reaches the offer stage. Relationships Typed, directed edges that carry the connections syncs exist to model. Offers is specific to Lever and Relationships to Neo4j — each maps to any object or custom field on the other side.
Users Lever team members (recruiters, hiring managers) with configurable roles; can be created via POST /users, deactivated, and reactivated through the API. Properties Key-value attributes on both nodes and relationships, mapped from source fields. Users is specific to Lever and Properties to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between Lever 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.

Lever Neo4j Sub-second propagation

DetectionLever notifies Stacksync of record changes through webhook events. Webhooks for candidate and application lifecycle events (applicationCreated, candidateStageChange, candidateArchiveStateChange, candidateHired,.

DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.

Neo4j Lever 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 Lever through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Lever: 10 requests/second per API key with a token-bucket burst to ~20/s; POSTs that create candidates/applications are throttled to roughly 2/second. Sustained overage returns 429 with Retry-After. List endpoints are cursor-paginated at up to 100 records per page.
What ships with Lever ⇄ Neo4j

Connect Lever and Neo4j for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Lever–Neo4j connection.

Real-time

Two-way sync

Changes in Lever or Neo4j instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Lever 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 Lever or Neo4j record.

Observability

Monitoring

Track your Lever ⇄ Neo4j sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Lever and Neo4j.

How the Lever and Neo4j connectors work

Lever

Integration surface
REST Data API (api.lever.co/v1)
Authentication
API key over HTTP Basic auth (key as username, blank password) for internal integrations, or OAuth 2.0 with 1-hour access tokens for partner integrations (auth.lever.co)
Change detection
Webhooks for candidate and application lifecycle events (applicationCreated, candidateStageChange, candidateArchiveStateChange, candidateHired, interview created/updated/deleted), plus incremental polling via created_at and updated_at range filters on Opportunities
Capabilities
read · write · webhooks
Rate limits
10 requests/second per API key with a token-bucket burst to ~20/s; POSTs that create candidates/applications are throttled to roughly 2/second. Sustained overage returns 429 with Retry-After. List endpoints are cursor-paginated at up to 100 records per page.
Lever setup guide

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 Lever 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.

  1. 01

    Connect your apps

    Authenticate Lever 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Lever connected
    Neo4j connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Lever 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Lever ⇄ Neo4j
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Lever Neo4j
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Lever and Neo4j integration FAQ

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.

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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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 517 integrations available for Lever and Neo4j.

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