Two-way sync
Changes in Neo4j or Rillet instantly reflect in both systems. No stale data, no manual imports.
Keep Neo4j and Rillet in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Engineers need finance data more often than finance systems make it easy to get: for internal tools, reporting services, or logic that reacts to invoices and payments. Working through the vendor API means rate limits, pagination, and glue code that has to be maintained forever.
Stacksync mirrors Invoice Payment, Charge, Reimbursement, Custom Field from Rillet into Nodes, Relationships, Properties, Labels in Neo4j and keeps the two in sync bi-directionally and in real time. Your services read finance records with normal queries against Neo4j, and rows your code writes or updates flow back into Rillet with validation, so the finance system stays the system of record.
Build dashboards and back-office tools directly on Neo4j; Stacksync handles the API calls, rate limits, and retries against Rillet.
Updates written to the synced tables in Neo4j propagate into Rillet, so automations can create or correct finance records without custom integration code.
Changes in Rillet appear in Neo4j as row changes, so you can trigger downstream logic with the database tooling you already use.
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 | Rillet objects | How this pairing syncs | |
|---|---|---|---|
| Relationships Typed, directed edges that carry the connections syncs exist to model. | Journal Entry Synced with incremental and full sync per the Stacksync docs. | Relationships is specific to Neo4j and Journal Entry to Rillet — each maps to any object or custom field on the other side. | |
| Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Invoice Payment Synced with incremental and full sync per the Stacksync docs. | Properties is specific to Neo4j and Invoice Payment to Rillet — each maps to any object or custom field on the other side. | |
| Labels Node type markers used to map source tables or objects onto the graph. | Charge Synced with incremental and full sync per the Stacksync docs. | Labels is specific to Neo4j and Charge to Rillet — each maps to any object or custom field on the other side. | |
| Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. | Reimbursement Synced with incremental and full sync per the Stacksync docs. | Indexes & Constraints is specific to Neo4j and Reimbursement to Rillet — each maps to any object or custom field on the other side. | |
| Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Custom Field Synced with incremental and full sync per the Stacksync docs. | Databases is specific to Neo4j and Custom Field to Rillet — each maps to any object or custom field on the other side. | |
| Users & Roles Security principals controlling what an integration credential can query or modify. | Account Synced with incremental and full sync per the Stacksync docs. | Users & Roles is specific to Neo4j and Account to Rillet — each maps to any object or custom field on the other side. |
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.
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 written to Rillet through its API, with automatic retries and rate-limit backoff.
DetectionRillet pushes changes as they happen — webhook events backed by change data capture. Near real-time updates via change tracking.
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Neo4j–Rillet connection.
Changes in Neo4j or Rillet instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Neo4j or Rillet data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Neo4j or Rillet record.
Track your Neo4j ⇄ Rillet sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Neo4j and Rillet.
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.
Authenticate Neo4j and Rillet with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Neo4j and Rillet 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Neo4j and Rillet: authenticate both systems, choose the objects to sync (such as Neo4j's Relationships and Properties), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Neo4j and Rillet. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Neo4j: Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties. On Rillet: Near real-time updates via change tracking; incremental sync per object, with delete detection (some objects checked every 1h or 4h). Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Rillet side: Invoice Payment, Charge, Reimbursement, Custom Field, plus custom fields where Rillet exposes them. On the Neo4j side: Nodes, Relationships, Properties, Labels. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for Neo4j and Rillet: Internal tools without API plumbing; Write back safely; React to financial events. Build dashboards and back-office tools directly on Neo4j; Stacksync handles the API calls, rate limits, and retries against Rillet.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 438 integrations available for Neo4j and Rillet.