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Database ⇄ Data warehouse

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

Keep Neo4j and Yellowbrick 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 Neo4j and Yellowbrick

Connect Neo4j and Yellowbrick with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Neo4j's rows in Yellowbrick, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Neo4j where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Neo4j sync into Yellowbrick in real time, and result tables in Yellowbrick sync back into Neo4j, with schema and type mapping between the two systems handled for you.

Common use cases

  • Sync CRM and marketing data into Yellowbrick tables so it can be joined with large fact tables for enterprise BI.
  • Land ERP transactional extracts in Yellowbrick for finance and supply-chain analytics.
  • Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
  • Sync product catalog and order history into Neo4j to power recommendation queries.

Offload heavy reads

Point analytical queries at the synced copy in Yellowbrick and keep Neo4j focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Neo4j land in Yellowbrick as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Yellowbrick sync into Neo4j, where whatever reads from that database gets them without querying the warehouse.

What you can sync between Neo4j and Yellowbrick

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 Yellowbrick objects
Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Schemas Namespaces used to organize synced datasets by source or domain.
Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Tables Columnar MPP tables; the primary targets for warehouse syncs.
Users & Roles Security principals controlling what an integration credential can query or modify. Views Logical views used to shape reads for BI and downstream syncs.
Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Users and Roles Access-control objects that govern what a sync service account can read and write.
Relationships Typed, directed edges that carry the connections syncs exist to model. Databases Top-level containers for schemas and tables.
What ships with Neo4j ⇄ Yellowbrick

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Neo4j or Yellowbrick 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 Yellowbrick record.

Observability

Monitoring

Track your Neo4j ⇄ Yellowbrick 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 Yellowbrick.

How the Neo4j and Yellowbrick 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

Yellowbrick

Integration surface
SQL wire protocol (PostgreSQL-compatible) with JDBC/ODBC drivers; bulk loading via the ybload utility
Authentication
Database credentials, with LDAP and Kerberos options in enterprise deployments
Change detection
Polling on timestamp columns; no exposed transaction-log CDC
Capabilities
read · write
Rate limits
No API rate limits; throughput depends on cluster sizing, and bulk loads should use ybload rather than row-by-row inserts.
How it works

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

    Choose tables

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

Neo4j and Yellowbrick integration FAQ

SECURITY

Security teams love 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 386 integrations available for Neo4j and Yellowbrick.

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