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Dynamo DB to Neo4j integration — real-time, two-way sync

Keep Dynamo DB 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 Dynamo DB and Neo4j

Keep Dynamo DB 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 Dynamo DB 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 Mirror SaaS objects into DynamoDB items to serve low-latency lookups from production services.
  • 02 Consolidate multi-region Global Tables data into a single reporting store.
  • 03 Sync product catalog and order history into Neo4j to power recommendation queries.
  • 04 Feed identity and access data into a graph for entitlement and blast-radius analysis.

Common sync patterns

Cross-engine sync

Keep the same dataset live in both Dynamo DB 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 Dynamo DB 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.

Dynamo DB objects Neo4j objects How this pairing syncs
Global Tables Multi-region replicas relevant when syncs must read from a specific region. Labels Node type markers used to map source tables or objects onto the graph. Global Tables is specific to Dynamo DB and Labels to Neo4j — each maps to any object or custom field on the other side.
Tables The top-level containers a sync targets; each table is addressed independently. Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Tables is specific to Dynamo DB and Indexes & Constraints to Neo4j — each maps to any object or custom field on the other side.
Items Schemaless records keyed by partition (and optional sort) key, mapped to rows or SaaS objects in syncs. Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Items is specific to Dynamo DB and Databases to Neo4j — each maps to any object or custom field on the other side.
Attributes Per-item fields, including nested maps and lists, flattened or mapped during sync. Users & Roles Security principals controlling what an integration credential can query or modify. Attributes is specific to Dynamo DB and Users & Roles to Neo4j — each maps to any object or custom field on the other side.
Partition and Sort Keys The primary key pair used as the match key for bi-directional sync. Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Partition and Sort Keys is specific to Dynamo DB and Nodes to Neo4j — each maps to any object or custom field on the other side.
Global Secondary Indexes Alternate access paths used when sync queries filter on non-key attributes. Relationships Typed, directed edges that carry the connections syncs exist to model. Global Secondary Indexes is specific to Dynamo DB and Relationships to Neo4j — each maps to any object or custom field on the other side.

How changes propagate between Dynamo DB 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.

Dynamo DB Neo4j Sub-second propagation

DetectionChanges in Dynamo DB are captured at the source via change data capture — no polling loop against its API. Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration.

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

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

Rate-limit considerations

  • Dynamo DB: Throughput is governed by the table's provisioned or on-demand capacity mode.
What ships with Dynamo DB ⇄ Neo4j

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Dynamo DB 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 Dynamo DB or Neo4j record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Dynamo DB and Neo4j.

How the Dynamo DB and Neo4j connectors work

Dynamo DB

Integration surface
Proprietary JSON-over-HTTPS API accessed through AWS SDKs; PartiQL supported for SQL-like queries
Authentication
AWS IAM credentials with SigV4 request signing
Change detection
Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration
Capabilities
read · write · CDC
Rate limits
Throughput is governed by the table's provisioned or on-demand capacity mode

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 Dynamo DB 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 Dynamo DB 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
    Dynamo DB connected
    Neo4j connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Dynamo DB 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 461 integrations available for Dynamo DB and Neo4j.

Popular · 6 of 461
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