Skip to content
Database ⇄ CRM

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

Keep Neo4j and Xactly 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 Xactly

Treat Xactly like part of your database: its records live in Neo4j as real tables, and writes in either place sync to the other in seconds.

Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in Neo4j, where it can be queried and joined like everything else.

Stacksync mirrors Products & Customers, Orders, Credits, Transactions (Commission & Bonus) from Xactly into Databases, Users & Roles, Nodes, Relationships in Neo4j with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Xactly with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.

Common use cases

  • 01 Mirror commission Transactions and Credits into a data warehouse to power rep-facing dashboards and comp-plan analytics without manual exports.
  • 02 Sync Participants, Positions, Titles, and Quotas from an HRIS/HCM and planning tools into Xactly so the org hierarchy and targets stay aligned with headcount changes.
  • 03 Write computed relationship scores (fraud, influence, similarity) back to operational systems.
  • 04 Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.

Common sync patterns

Internal tools without API code

Back-office apps read and write the synced tables; Stacksync handles the Xactly API, limits, and retries.

Trigger workflows from CRM changes

Field and stage updates in Xactly arrive as row changes in Neo4j, ready to drive jobs and notifications.

Query the CRM like a database

Accounts, contacts, and custom objects from Xactly become tables in Neo4j you can join with application data directly.

What you can sync between Neo4j and Xactly

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 Xactly objects How this pairing syncs
Labels Node type markers used to map source tables or objects onto the graph. Products & Customers Product and customer/account master used in crediting rules and reporting; loaded and updated from CRM/ERP through Connect (write) and read for lookups, so read and write. Labels is specific to Neo4j and Products & Customers to Xactly — each maps to any object or custom field on the other side.
Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Orders Sales order and transaction records loaded into Incent as the raw input for crediting and calculation; created and updated through Connect load and ETL steps (write) and read back for reconciliation, so read and write. Indexes & Constraints is specific to Neo4j and Orders to Xactly — each maps to any object or custom field on the other side.
Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Credits Crediting records that tie an order to a participant and position; system-calculated credits are read, while manual and adjustment credits are loaded through Connect, so read and write. Databases is specific to Neo4j and Credits to Xactly — each maps to any object or custom field on the other side.
Users & Roles Security principals controlling what an integration credential can query or modify. Transactions (Commission & Bonus) Calculated commission and bonus line items produced by Incent's calculation engine; read as the output of comp runs for reporting and downstream payout, so effectively read-only results. Users & Roles is specific to Neo4j and Transactions (Commission & Bonus) to Xactly — each maps to any object or custom field on the other side.
Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Participants (Payees) Sales reps and payees keyed to positions; loaded and updated from HRIS/HCM source data through Connect (write) and read for roster reporting, so read and write. Nodes is specific to Neo4j and Participants (Payees) to Xactly — each maps to any object or custom field on the other side.
Relationships Typed, directed edges that carry the connections syncs exist to model. Positions & Titles Org-hierarchy positions and titles that credits and quotas roll up to; loaded and maintained through Connect (write) and read to resolve the hierarchy, so read and write. Relationships is specific to Neo4j and Positions & Titles to Xactly — each maps to any object or custom field on the other side.

How changes propagate between Neo4j and Xactly

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.

Neo4j Xactly 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 Xactly as a row-level write, with types converted between the two schemas.

Xactly Neo4j Interval-based propagation

DetectionStacksync polls Xactly for changes on an incremental schedule, reading only records changed since the previous pass. No CDC log for external tools to consume.

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

Rate-limit considerations

  • Xactly: Xactly does not publish numeric per-second rate limits. The Connect platform enforces query concurrency and long-running-query limits, so large extracts are paged and heavy loads/queries run as asynchronous Connect jobs (submit, then retrieve results) rather than row-by-row calls; batch loads are the supported path for high volume.
What ships with Neo4j ⇄ Xactly

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Neo4j or Xactly 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 Xactly record.

Observability

Monitoring

Track your Neo4j ⇄ Xactly 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 Xactly.

How the Neo4j and Xactly 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

Xactly

Integration surface
Xactly Connect REST API v2 (JSON), plus ODBC/JDBC drivers over the same ANSI-SQL data model. Incent data is exposed as SQL-queryable objects (for example xactly_order, xactly_credit, xactly_transaction, xactly_payment); data is loaded and extracted through Connect load/query steps and server-side ETL Pipelines. The base host is region/pod-specific (for example https://<pod>.xactlycorp.com).
Authentication
OAuth 2.0 via the Xactly Connect API Gateway (bearer tokens issued on behalf of an Xactly Incent user), with HTTP Basic authentication using a dedicated Xactly Connect service-user's credentials also supported for the Connect REST API v2. The connecting user needs Connect/API access plus the relevant object permissions in Incent.
Change detection
No CDC log for external tools to consume. Incremental sync uses SQL predicates on modified/last-updated timestamp columns (for example WHERE modified_date > watermark) against Connect's queryable objects, or scheduled Connect ETL Pipelines that pull deltas since the last run. Xactly Connect has no outbound HTTP webhooks, so change detection is pull/ETL-based.
Capabilities
read · write
Rate limits
Xactly does not publish numeric per-second rate limits. The Connect platform enforces query concurrency and long-running-query limits, so large extracts are paged and heavy loads/queries run as asynchronous Connect jobs (submit, then retrieve results) rather than row-by-row calls; batch loads are the supported path for high volume.
Xactly setup guide
How it works

How to connect Neo4j to Xactly — 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 Neo4j and Xactly 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
    Neo4j connected
    Xactly connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Neo4j and Xactly 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 · Neo4j ⇄ Xactly
    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
    Neo4j Xactly
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Neo4j and Xactly 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.

Learn more about security
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:

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 540 integrations available for Neo4j and Xactly.

Popular · 8 of 540
All Neo4j integrations All Xactly integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own