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Data warehouse ⇄ Database

Apache Doris to Neo4j integration — real-time, two-way sync

Keep Apache Doris 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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Why teams connect Apache Doris and Neo4j

Connect Neo4j and Apache Doris 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 Apache Doris, 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 Apache Doris in real time, and result tables in Apache Doris sync back into Neo4j, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Continuously upsert changing records into Unique Key tables so analytics reflect current state rather than append-only history.
  • 02 Read aggregates from Doris and sync them into business tools like CRMs or spreadsheets.
  • 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

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

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

Operational data in the warehouse, minus the pipeline

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

What you can sync between Apache Doris 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.

Apache Doris objects Neo4j objects How this pairing syncs
Databases Logical containers that scope connections and grants. Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Partitions Range or list partitions that bound incremental loads. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Partitions is specific to Apache Doris and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side.
Materialized Views Precomputed views readable for downstream syncs and BI. Users & Roles Security principals controlling what an integration credential can query or modify. Materialized Views is specific to Apache Doris and Users & Roles to Neo4j — each maps to any object or custom field on the other side.
Users and Roles Principals used to grant the sync connection scoped access. Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Users and Roles is specific to Apache Doris and Nodes to Neo4j — each maps to any object or custom field on the other side.
Tables Columnar tables in one of Doris's table models, used as sync destinations. Relationships Typed, directed edges that carry the connections syncs exist to model. Tables is specific to Apache Doris and Relationships to Neo4j — each maps to any object or custom field on the other side.
Unique Key Tables Tables supporting primary-key upserts, the natural target for row-level syncs. Properties Key-value attributes on both nodes and relationships, mapped from source fields. Unique Key Tables is specific to Apache Doris and Properties to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between Apache Doris 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.

Apache Doris Neo4j Interval-based propagation

DetectionStacksync polls Apache Doris for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition or timestamp columns for reads.

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

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

Rate-limit considerations

  • Apache Doris: No API quotas; load throughput depends on cluster resources and load-job configuration.
What ships with Apache Doris ⇄ Neo4j

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Doris 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 Apache Doris or Neo4j record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Apache Doris and Neo4j connectors work

Apache Doris

Integration surface
MySQL wire protocol for SQL access; HTTP APIs (such as Stream Load) for bulk ingestion
Authentication
Database credentials
Change detection
Polling on partition or timestamp columns for reads; ingestion into Doris is push-based via load jobs
Capabilities
read · write
Rate limits
No API quotas; load throughput depends on cluster resources and load-job configuration

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

    Choose tables

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

Apache Doris 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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ISO 27001
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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 447 integrations available for Apache Doris and Neo4j.

Popular · 6 of 447
All Apache Doris integrations All Neo4j integrations Browse all integrations
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