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CRM ⇄ Database

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

Keep DealCloud 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 DealCloud and Neo4j

Treat DealCloud 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 Activity, Task, User, Deal from DealCloud 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 DealCloud 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 Keep DealCloud contacts and relationships in sync with an enrichment or email platform to maintain accurate firm-wide relationship intelligence.
  • 02 Mirror DealCloud activities and tasks into an operational database to power internal dashboards without hitting the API on every read.
  • 03 Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
  • 04 Sync product catalog and order history into Neo4j to power recommendation queries.

Common sync patterns

Product events onto CRM records

Signup, usage, or lifecycle changes written to Neo4j sync onto the matching records in DealCloud, giving go-to-market teams live product context.

Internal tools without API code

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

Trigger workflows from CRM changes

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

What you can sync between DealCloud 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.

DealCloud objects Neo4j objects How this pairing syncs
Relationship Synced with incremental and full sync. Relationships Typed, directed edges that carry the connections syncs exist to model. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Contact Synced with incremental and full sync. Users & Roles Security principals controlling what an integration credential can query or modify. Contact is specific to DealCloud and Users & Roles to Neo4j — each maps to any object or custom field on the other side.
Fund Synced with incremental and full sync. Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Fund is specific to DealCloud and Nodes to Neo4j — each maps to any object or custom field on the other side.
Investment Synced with incremental and full sync. Properties Key-value attributes on both nodes and relationships, mapped from source fields. Investment is specific to DealCloud and Properties to Neo4j — each maps to any object or custom field on the other side.
Activity Synced with incremental and full sync. Labels Node type markers used to map source tables or objects onto the graph. Activity is specific to DealCloud and Labels to Neo4j — each maps to any object or custom field on the other side.
Task Synced with incremental and full sync. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Task is specific to DealCloud and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between DealCloud 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.

DealCloud Neo4j Interval-based propagation

DetectionStacksync polls DealCloud for changes on an incremental schedule, reading only records changed since the previous pass. Incremental via each entry's last-modified timestamp.

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

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

Rate-limit considerations

  • DealCloud: API request limits apply per firm tenant; Stacksync manages throttling and retries automatically.
What ships with DealCloud ⇄ Neo4j

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DealCloud 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 DealCloud or Neo4j record.

Observability

Monitoring

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

Trading partners

EDI

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

How the DealCloud and Neo4j connectors work

DealCloud

Integration surface
REST API (DealCloud Data API v2)
Authentication
OAuth 2.0 client-credentials; a DealCloud administrator generates a client ID and secret in the DealCloud admin API settings and grants Stacksync the required scopes
Change detection
Incremental via each entry's last-modified timestamp; DealCloud has no universal native change-data-capture, so Stacksync polls modified rows on an interval
Capabilities
read · write
Rate limits
API request limits apply per firm tenant; Stacksync manages throttling and retries automatically.

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

    Choose tables

    Pick the DealCloud 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 · DealCloud ⇄ 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
    DealCloud Neo4j
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

DealCloud 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.

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 392 integrations available for DealCloud and Neo4j.

Popular · 8 of 392
All DealCloud integrations All Neo4j integrations Browse all integrations
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