Real-time
Two-way sync
Changes in Google Pubsub or Neo4j instantly reflect in both systems. No stale data, no manual imports.
Developer tools ⇄ Database
Google Pubsub to Neo4j integration — real-time, two-way sync
Keep Google Pubsub 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 Google Pubsub and Neo4j
Keep Neo4j and Google Pubsub in step: the rows in your database and the Message attributes, Dead-letter topics, Ordering keys, Topics your engineering tools track stay consistent in real time, in both directions.
Neo4j is where your application's durable data lives; Google Pubsub is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.
Stacksync syncs Relationships, Properties, Labels, Indexes & Constraints in Neo4j with Message attributes, Dead-letter topics, Ordering keys, Topics in Google Pubsub field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.
Common use cases
- 01 Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
- 02 Sync product catalog and order history into Neo4j to power recommendation queries.
- 03 Publish new and changed database rows as messages to a Pub/Sub topic so multiple downstream subscriptions consume the change stream independently.
- 04 Consume messages from a subscription via StreamingPull and write them into a Postgres or warehouse table for durable, SQL-queryable storage.
Common sync patterns
React to changes on either side in near real time
Updates in Google Pubsub arrive as row changes in Neo4j, and writes to Neo4j propagate to Google Pubsub within seconds, so triggers, jobs, and alerts fire without polling.
Where Google Pubsub manages users or groups: keep identity aligned
Directory and identity records in Google Pubsub stay matched to the users or owners table in Neo4j, so provisioning and de-provisioning flow from one source.
Turn rows into the records your tools track
A new or changed row in Neo4j creates or updates the matching record in Google Pubsub, whether that is an issue, an event, a message, or a user, so the tool reflects the database without a custom API job.
What you can sync between Google Pubsub 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.
| Google Pubsub objects | Neo4j objects | How this pairing syncs | |
|---|---|---|---|
| Schemas Avro or Protocol Buffer definitions bound to a topic; validate that every published message matches the agreed structure. | Databases Named databases in a single instance that scope multi-tenant or multi-domain syncs. | Schemas is specific to Google Pubsub and Databases to Neo4j — each maps to any object or custom field on the other side. | |
| Snapshots Captured subscription state for seek/replay; lets already-acknowledged messages be redelivered from a point in time. | Users & Roles Security principals controlling what an integration credential can query or modify. | Snapshots is specific to Google Pubsub and Users & Roles to Neo4j — each maps to any object or custom field on the other side. | |
| Message attributes Up to 100 key-value pairs per message; carry routing metadata and drive subscription filter expressions. | Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | Message attributes is specific to Google Pubsub and Nodes to Neo4j — each maps to any object or custom field on the other side. | |
| Dead-letter topics Destination for messages that exceed a subscription's max delivery attempts; isolates poison messages for later handling. | Relationships Typed, directed edges that carry the connections syncs exist to model. | Dead-letter topics is specific to Google Pubsub and Relationships to Neo4j — each maps to any object or custom field on the other side. | |
| Ordering keys Tag messages so those sharing a key deliver in publish order when message ordering is enabled; throughput capped at 1 MBps per key. | Properties Key-value attributes on both nodes and relationships, mapped from source fields. | Ordering keys is specific to Google Pubsub and Properties to Neo4j — each maps to any object or custom field on the other side. | |
| Topics Named resource publishers send to; Stacksync publishes each record change as a message to a topic for downstream subscribers to consume. | Labels Node type markers used to map source tables or objects onto the graph. | Topics is specific to Google Pubsub and Labels to Neo4j — each maps to any object or custom field on the other side. |
How changes propagate between Google Pubsub 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.
Google Pubsub Neo4j Sub-second propagation
DetectionGoogle Pubsub notifies Stacksync of record changes through webhook events. Consumes messages as they arrive on a subscription — StreamingPull (long-lived gRPC) or a push subscription delivering each message as an HTTPS POST.
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Neo4j Google Pubsub 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 written to Google Pubsub through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Google Pubsub: Per-region throughput quotas (publish up to ~4 GB/s in large regions); 10 MB max per message and per publish request, 1,000 messages per request, and 1 MBps per ordering key.
What ships with Google Pubsub ⇄ Neo4j
Connect Google Pubsub and Neo4j for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Pubsub–Neo4j connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Google Pubsub 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 Google Pubsub or Neo4j record.
Observability
Monitoring
Track your Google Pubsub ⇄ Neo4j sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Google Pubsub and Neo4j.
How the Google Pubsub and Neo4j connectors work
Google Pubsub
- Integration surface
- REST and gRPC (Cloud Pub/Sub API v1)
- Authentication
- Google Cloud IAM via OAuth 2.0 / service-account credentials (JSON key or workload identity); requires roles such as pubsub.publisher and pubsub.subscriber
- Change detection
- Consumes messages as they arrive on a subscription — StreamingPull (long-lived gRPC) or a push subscription delivering each message as an HTTPS POST; no modified-date polling
- Capabilities
- read · write · webhooks
- Rate limits
- Per-region throughput quotas (publish up to ~4 GB/s in large regions); 10 MB max per message and per publish request, 1,000 messages per request, and 1 MBps per ordering key
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 Google Pubsub 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 Google Pubsub 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.
Google Pubsub
connected
Neo4j
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Google Pubsub 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 · Google Pubsub ⇄ 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.
Google Pubsub Neo4jCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Google Pubsub and Neo4j integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Google Pubsub and Neo4j: authenticate both systems, choose the objects to sync (such as Google Pubsub's Schemas and Snapshots), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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 Google Pubsub 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 Google Pubsub and Neo4j connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Google Pubsub–Neo4j integration in-house.
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Yes — Stacksync ships production-grade connectors for both Google Pubsub and Neo4j. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Google Pubsub: Consumes messages as they arrive on a subscription — StreamingPull (long-lived gRPC) or a push subscription delivering each message as an HTTPS POST; no modified-date polling. On Neo4j: Neo4j Change Data Capture on Enterprise and Aura streams graph changes; otherwise Cypher polling on timestamp properties. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Neo4j side: Relationships, Properties, Labels, Indexes & Constraints, plus custom fields where Neo4j exposes them. On the Google Pubsub side: Message attributes, Dead-letter topics, Ordering keys, Topics. Stacksync auto-detects both schemas and converts types between the two systems.
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.
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 329 integrations available for Google Pubsub and Neo4j.
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