Real-time
Two-way sync
Changes in Dremio or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Dremio to Neo4j integration — real-time, two-way sync
Keep Dremio 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
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Dremio and Neo4j
Connect Neo4j and Dremio 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 Dremio, 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 Dremio in real time, and result tables in Dremio sync back into Neo4j, with schema and type mapping between the two systems handled for you.
Common use cases
- Reverse-ETL aggregates computed over lake data out to CRMs and finance tools for business users.
- Publish operational database tables into Iceberg via Dremio so the lakehouse reflects current application state.
- Write computed relationship scores (fraud, influence, similarity) back to operational systems.
- Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.
Serve warehouse results at database speed
Aggregates or model outputs computed in Dremio sync into Neo4j, where whatever reads from that database gets them without querying the warehouse.
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 Dremio and keep Neo4j focused on its operational workload.
What you can sync between Dremio 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.
| Dremio objects | Neo4j objects | |
|---|---|---|
| Spaces and folders Namespaces that organize virtual datasets and govern access. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | |
| Reflections Materialized accelerations that make repeated extraction queries cheaper. | Labels Node type markers used to map source tables or objects onto the graph. | |
| Jobs Query execution records useful for monitoring sync workloads. | Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | |
| Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | |
| Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. | Users & Roles Security principals controlling what an integration credential can query or modify. | |
| Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. | Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. |
What ships with Dremio ⇄ Neo4j
Connect Dremio and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Dremio 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 Dremio or Neo4j record.
Observability
Monitoring
Track your Dremio ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Dremio and Neo4j.
How the Dremio and Neo4j connectors work
Dremio
- Integration surface
- Arrow Flight SQL, JDBC/ODBC, and a REST API
- Authentication
- Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
- Change detection
- Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Bounded by engine capacity and workload management rather than API rate limits
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 Dremio 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 Dremio 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.
Dremio
connected
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Dremio 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 · Dremio ⇄ 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.
Dremio Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Dremio and Neo4j integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Dremio and Neo4j: authenticate both systems, choose the objects to sync (such as Dremio's Spaces and folders and Reflections), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Common patterns for Dremio and Neo4j: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in Dremio sync into Neo4j, where whatever reads from that database gets them without querying the warehouse.
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Dremio: Arrow Flight SQL, JDBC/ODBC, and a REST API. Authentication: Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud. Neo4j: Bolt binary protocol with Cypher via official drivers, plus an HTTP query API. Authentication: Username/password (basic auth); enterprise deployments add SSO options. Stacksync manages authentication, retries, and rate limits on both sides.
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Dremio: Arrow Flight SQL is a first-class endpoint designed for high-throughput columnar result transfer, an alternative to JDBC/ODBC for large extracts. Neo4j: Neo4j uses a property graph model in which nodes and relationships both carry key-value properties, so edges hold data rather than just linking rows. Stacksync's field mapping accounts for these differences between Dremio and Neo4j without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Dremio and Neo4j records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Dremio and Neo4j connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Dremio–Neo4j integration in-house.
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.
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
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Dremio and Neo4j.
Popular · 8 of 386
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Dremio ⇄ IBM Db2 -
Dremio ⇄ Firebase -
Dremio ⇄ SingleStore -
Dremio ⇄ Amazon Aurora - Neo4j ⇄ Amazon Redshift
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Neo4j ⇄ Apache Doris -
Neo4j ⇄ Apache Druid -
Neo4j ⇄ Apache Hive
No integrations match .
