Real-time
Real-time sync
Changes in Crustdata or Neo4j instantly reflect in both systems. No stale data, no manual imports.
CRM ⇄ Database
Crustdata to Neo4j integration — real-time data sync
Keep Crustdata 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
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Adopted by fast-scaling companies moving mission-critical data in real time
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Migrated from MuleSoft
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Crustdata and Neo4j
Treat Crustdata like part of your database: its records live in Neo4j as real tables, and writes in either place sync to the other in seconds.
Crustdata is a read-only source: Stacksync reads its data in real time and delivers it into Neo4j, so Neo4j always reflects the current state of Crustdata — without exports, scripts, or schedulers.
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.
Common use cases
- 01 Stream screener results into a warehouse to maintain a living TAM and target-account universe.
- 02 Append enrichment at lead-capture time so new records arrive scored and routable.
- 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
Product events onto CRM records
Signup, usage, or lifecycle changes written to Neo4j sync onto the matching records in Crustdata, 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 Crustdata API, limits, and retries.
Trigger workflows from CRM changes
Field and stage updates in Crustdata arrive as row changes in Neo4j, ready to drive jobs and notifications.
What you can sync between Crustdata 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.
| Crustdata objects | Neo4j objects | How this pairing syncs | |
|---|---|---|---|
| Headcount and Growth Metrics Time-series employee counts by department and region; read to score accounts on hiring momentum and expansion signals. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Headcount and Growth Metrics is specific to Crustdata and Properties to Neo4j — each maps to any object or custom field on the other side. | |
| Tech Stack Detected technologies per company; read to build segments and route accounts by the tools they already use. | Labels Node type markers used to map source tables or objects onto the graph. | Tech Stack is specific to Crustdata and Labels to Neo4j — each maps to any object or custom field on the other side. | |
| Screener Results Saved company searches with filter criteria; read on a schedule so target-account lists in the CRM refresh as companies enter the criteria. | Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | Screener Results is specific to Crustdata and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side. | |
| Enrichment Responses Real-time enrichment lookups keyed by domain or profile URL; read to append fresh firmographic and contact data at form-fill or record-creation time. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Enrichment Responses is specific to Crustdata and Databases to Neo4j — each maps to any object or custom field on the other side. | |
| Companies Firmographic records — industry, size, funding, growth signals; read out to enrich CRM accounts and warehouse company tables. | Users & Roles Security principals controlling what an integration credential can query or modify. | Companies is specific to Crustdata and Users & Roles to Neo4j — each maps to any object or custom field on the other side. | |
| People Contact and profile data for decision-makers; read into a CRM or outreach tool to fill missing titles, emails, and LinkedIn profiles. | Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | People is specific to Crustdata and Nodes to Neo4j — each maps to any object or custom field on the other side. |
How changes propagate between Crustdata 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.
Crustdata Neo4j Interval-based propagation
DetectionStacksync polls Crustdata for changes on an incremental schedule, reading only records changed since the previous pass. Pull-based: real-time enrichment endpoints for on-demand lookups plus periodic re-pulls of screeners and datasets.
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Neo4j Crustdata 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.
DeliveryCrustdata does not accept inbound record writes, so this direction carries requests rather than records: Crustdata's output flows back as field updates on the originating Neo4j records.
Rate-limit considerations
- Crustdata: Requests are metered by plan credits and per-minute rate limits; bulk dataset pulls are the efficient path for large refreshes rather than per-record enrichment calls.
What ships with Crustdata ⇄ Neo4j
Connect Crustdata and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Crustdata–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Crustdata 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 Crustdata or Neo4j record.
Observability
Monitoring
Track your Crustdata ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Crustdata and Neo4j.
How the Crustdata and Neo4j connectors work
Crustdata
- Integration surface
- REST API (JSON)
- Authentication
- API token — Authorization: Token header issued per workspace
- Change detection
- Pull-based: real-time enrichment endpoints for on-demand lookups plus periodic re-pulls of screeners and datasets; no webhooks or change feed
- Capabilities
- read
- Rate limits
- Requests are metered by plan credits and per-minute rate limits; bulk dataset pulls are the efficient path for large refreshes rather than per-record enrichment calls.
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 Crustdata 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 Crustdata 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.
Crustdata
connected
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Crustdata 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 · Crustdata ⇄ 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.
Crustdata Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Crustdata and Neo4j integration FAQ
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Yes. Stacksync provides a managed, real-time integration between Crustdata and Neo4j — Crustdata is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Crustdata 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 Crustdata: Pull-based: real-time enrichment endpoints for on-demand lookups plus periodic re-pulls of screeners and datasets; no webhooks or change feed. 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.
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On the Crustdata side: Tech Stack, Screener Results, Enrichment Responses, Companies, plus custom fields where Crustdata exposes them. On the Neo4j side: Databases, Users & Roles, Nodes, Relationships. Stacksync auto-detects both schemas and converts types between the two systems.
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Crustdata is a read-only source, so this integration runs one-way: Stacksync reads from Crustdata in real time and delivers into Neo4j. Field mapping and monitoring work the same as for two-way pairs.
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Common patterns for Crustdata and Neo4j: Product events onto CRM records; Internal tools without API code; Trigger workflows from CRM changes. Signup, usage, or lifecycle changes written to Neo4j sync onto the matching records in Crustdata, giving go-to-market teams live product context.
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
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