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Amazon RDS to Neo4j integration — real-time, two-way sync

Keep Amazon RDS 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon RDS and Neo4j

Keep Amazon RDS and Neo4j 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 Amazon RDS and Neo4j 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

  • 01 Bi-directional sync between an RDS database and a CRM so application data and sales data stay consistent without custom integration code
  • 02 Mirror SaaS objects into RDS tables so product features can join business data with application data in one query
  • 03 Feed identity and access data into a graph for entitlement and blast-radius analysis.
  • 04 Write computed relationship scores (fraud, influence, similarity) back to operational systems.

Common sync patterns

Cross-engine sync

Keep the same dataset live in both Amazon RDS and Neo4j, 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 Amazon RDS 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.

Amazon RDS objects Neo4j objects How this pairing syncs
Databases Engine-level databases on the instance that scope a sync's reads and writes. 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.
Stored Procedures Engine-specific logic that can react to synced rows. Relationships Typed, directed edges that carry the connections syncs exist to model. Stored Procedures is specific to Amazon RDS and Relationships to Neo4j — each maps to any object or custom field on the other side.
Schemas Namespaces within a database used to isolate synced tables. Properties Key-value attributes on both nodes and relationships, mapped from source fields. Schemas is specific to Amazon RDS and Properties to Neo4j — each maps to any object or custom field on the other side.
Tables The core sync target; rows map to records in connected SaaS systems. Labels Node type markers used to map source tables or objects onto the graph. Tables is specific to Amazon RDS and Labels to Neo4j — each maps to any object or custom field on the other side.
Views Read-side projections exposed to outbound syncs. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Views is specific to Amazon RDS and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side.
Columns Field-level mapping targets, typed per the underlying engine. Users & Roles Security principals controlling what an integration credential can query or modify. Columns is specific to Amazon RDS and Users & Roles to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between Amazon RDS 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.

Amazon RDS Neo4j Sub-second propagation

DetectionChanges in Amazon RDS are captured at the source via change data capture — no polling loop against its API. Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC.

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

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

Rate-limit considerations

  • Amazon RDS: No API rate limits; throughput depends on instance class, storage IOPS, and connection limits.
What ships with Amazon RDS ⇄ Neo4j

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon RDS 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 Amazon RDS or Neo4j record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon RDS and Neo4j.

How the Amazon RDS and Neo4j connectors work

Amazon RDS

Integration surface
SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle)
Authentication
Database credentials over SSL/TLS, or IAM database authentication on supported engines
Change detection
Engine-native log-based CDC: MySQL/MariaDB binlog, PostgreSQL logical replication, SQL Server CDC; enabled through RDS parameter groups, with polling as a fallback
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput depends on instance class, storage IOPS, and connection 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 Amazon RDS 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 Amazon RDS 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
    Amazon RDS connected
    Neo4j connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Amazon RDS 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.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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 465 integrations available for Amazon RDS and Neo4j.

Popular · 5 of 465
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