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

Keep Neo4j and SingleStore 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
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Neo4j and SingleStore

Keep Neo4j and SingleStore synchronized in real time, across engines, regions, or services, in one or both directions.

Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.

Stacksync syncs tables or collections between Neo4j and SingleStore continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.

Common use cases

  • Write computed relationship scores (fraud, influence, similarity) back to operational systems.
  • Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.
  • Feed synced operational data into applications that need low-latency responses over fresh data.
  • Mirror CRM and SaaS objects into SingleStore tables to serve low-latency operational dashboards.

Cross-engine sync

Keep the same dataset live in both Neo4j and SingleStore, so each workload runs on the engine that suits it.

Migration with zero-downtime cutover

When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

What you can sync between Neo4j and SingleStore

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 SingleStore objects
Relationships Typed, directed edges that carry the connections syncs exist to model. Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs.
Properties Key-value attributes on both nodes and relationships, mapped from source fields. Stored Procedures Existing logic sometimes invoked on write paths.
Labels Node type markers used to map source tables or objects onto the graph. Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys.
Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Databases The connection target containing the tables a sync addresses.
Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans.
Users & Roles Security principals controlling what an integration credential can query or modify. Views Read-only projections used as curated sync sources.
What ships with Neo4j ⇄ SingleStore

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Neo4j or SingleStore 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 SingleStore record.

Observability

Monitoring

Track your Neo4j ⇄ SingleStore 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 SingleStore.

How the Neo4j and SingleStore 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

SingleStore

Integration surface
SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
Authentication
Database credentials
Change detection
Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by workspace or cluster size
How it works

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

    Choose tables

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

Neo4j and SingleStore 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 SingleStore.

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