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

Keep Neo4j and TimescaleDB 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

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Why teams connect Neo4j and TimescaleDB

Keep Neo4j and TimescaleDB 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 TimescaleDB 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

  • Feed identity and access data into a graph for entitlement and blast-radius analysis.
  • Write computed relationship scores (fraud, influence, similarity) back to operational systems.
  • Consolidate metrics from several services into one hypertable to serve a single reporting layer.
  • Sync product or IoT telemetry stored in TimescaleDB into a CRM so account teams see usage metrics next to the customer record.

Cross-engine sync

Keep the same dataset live in both Neo4j and TimescaleDB, 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 TimescaleDB

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 TimescaleDB objects
Properties Key-value attributes on both nodes and relationships, mapped from source fields. Schemas Postgres namespaces used to separate synced datasets by team or environment.
Labels Node type markers used to map source tables or objects onto the graph. Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs.
Indexes & Constraints Uniqueness constraints and indexes that make MERGE-based upserts reliable and fast. Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly.
Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems.
Users & Roles Security principals controlling what an integration credential can query or modify. Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data.
Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. Views Standard SQL views used to shape or filter data for consumers.
What ships with Neo4j ⇄ TimescaleDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Neo4j or TimescaleDB 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 TimescaleDB record.

Observability

Monitoring

Track your Neo4j ⇄ TimescaleDB 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 TimescaleDB.

How the Neo4j and TimescaleDB 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

TimescaleDB

Integration surface
SQL wire protocol (PostgreSQL)
Authentication
Database credentials
Change detection
Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by database resources and connection limits.
How it works

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

    Choose tables

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

Neo4j and TimescaleDB 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 TimescaleDB.

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