Real-time
Two-way sync
Changes in Neo4j or Splunk instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Analytics
Neo4j to Splunk integration — real-time, two-way sync
Keep Neo4j and Splunk 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Neo4j and Splunk
Give Splunk the users, events, and records that live in Neo4j in real time, and sync the cohorts and scores Splunk computes back into Neo4j where your applications read them.
A database holds the rows your business runs on: the users, events, orders, and records that every service reads and writes. Splunk is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from Neo4j into Splunk usually means a hand-built extract or a change-data-capture pipeline that breaks the moment a column is renamed, and reporting that always trails last night's load.
Stacksync syncs Indexes & Constraints, Databases, Users & Roles, Nodes in Neo4j with Dashboards, Search Results, Saved Searches, Fired Alerts in Splunk in real time and in both directions. Operational rows flow into Splunk as they change, so dashboards read current data with no pipeline to maintain, and the segments, cohorts, or scores Splunk computes flow back into Neo4j, where the applications and services that read from it get them at normal query latency. Field-level mapping, schema and type translation, and conflict resolution are handled for you.
Common use cases
- 01 Export Users and Roles into an IAM database for periodic access reviews, or provision them from an identity source of truth.
- 02 Sync fired-alert history and saved-search definitions into Postgres so security and reliability teams query alert trends and detection coverage in SQL.
- 03 Keep a customer-360 graph continuously updated from ERP, CRM, and support sources.
- 04 Mirror CRM accounts and contacts into a graph to model buying-group and referral relationships.
Common sync patterns
Where Splunk builds cohorts or scores: results your services can read
Segments, cohorts, or scores computed in Splunk sync back into Neo4j, where the services that read from the database act on them at query speed without calling the analytics API.
Analytics on live operational data, minus the pipeline
The users, events, orders, and records stored in Neo4j land in Splunk as they change, so dashboards, funnels, and metrics run on current data instead of last night's extract.
One version of each user or account
A user, account, or record corrected in either system updates the other, so the identity your reports group by matches the identity your database stores.
What you can sync between Neo4j and Splunk
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 | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Users & Roles Security principals controlling what an integration credential can query or modify. | Search Results SPL searches dispatched via POST /services/search/jobs return a search ID (SID); results are pulled from /services/search/jobs/{sid}/results once the job completes, or synchronously via oneshot/export mode. The primary read path for streaming indexed events out to a warehouse. | Users & Roles is specific to Neo4j and Search Results to Splunk — each maps to any object or custom field on the other side. | |
| Nodes Entity records (customers, products, accounts) written from source systems as labeled nodes. | Saved Searches Scheduled searches, reports, and the definitions behind alerts at /services/saved/searches with full create, update, and delete. Read out for governance and coverage review, or provisioned and updated from a config source. | Nodes is specific to Neo4j and Saved Searches to Splunk — each maps to any object or custom field on the other side. | |
| Relationships Typed, directed edges that carry the connections syncs exist to model. | Fired Alerts Triggered alert instances listed at /services/alerts/fired_alerts; alert configuration (conditions, schedule, actions) lives on the corresponding saved search. Landed in a database for alert-trend and detection-coverage reporting. | Relationships is specific to Neo4j and Fired Alerts to Splunk — 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. | KV Store Collections App-scoped, MongoDB-backed key-value collections at /servicesNS/{owner}/{app}/storage/collections/data/{collection} with full CRUD and batch endpoints. Genuinely bidirectional lookup/state store — read records out or write records in. | Properties is specific to Neo4j and KV Store Collections to Splunk — 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. | Indexes Index inventory and settings (retention, max size, event counts) via /services/data/indexes, with create and edit; loaded into a database for capacity, retention, and data-onboarding tracking. | Labels is specific to Neo4j and Indexes to Splunk — 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. | HTTP Event Collector The write-in path: POST events and metrics to /services/collector (port 8088, or 443 on Splunk Cloud) authenticated with a per-input HEC token, so external records are indexed alongside logs for search and correlation. | Indexes & Constraints is specific to Neo4j and HTTP Event Collector to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between Neo4j and Splunk
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.
Neo4j Splunk 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 Splunk through its API, with automatic retries and rate-limit backoff.
Splunk Neo4j Sub-second propagation
DetectionSplunk notifies Stacksync of record changes through webhook events. Time-range searches over indexed events (earliest/latest on _time or _indextime).
DeliveryEach detected change is written to Neo4j through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Splunk: The management REST API throttles through search-concurrency quotas — max concurrent searches per user and role, plus per-CPU historical search limits in limits.conf — rather than a fixed per-request rate; exceeding quota queues or blocks jobs. HEC has per-token and per-instance throughput limits, and Splunk Cloud adds ingestion and API limits on top.
What ships with Neo4j ⇄ Splunk
Connect Neo4j and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Neo4j–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Neo4j or Splunk 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 Splunk record.
Observability
Monitoring
Track your Neo4j ⇄ Splunk 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 Splunk.
How the Neo4j and Splunk 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
Splunk
- Integration surface
- REST API (management API + HTTP Event Collector)
- Authentication
- HTTP Basic (username/password), or a session key from POST /services/auth/login sent as Authorization: Splunk <key>, or a bearer authentication token (Authorization: Bearer <token>). The HTTP Event Collector uses its own per-input token (Authorization: Splunk <hec-token>). Management API defaults to port 8089; HEC to port 8088 (443 on Splunk Cloud).
- Change detection
- Time-range searches over indexed events (earliest/latest on _time or _indextime); events are immutable once indexed, so incremental extraction advances a time cursor rather than a modified-date CDC feed. Config objects such as saved searches and KV Store are polled; alerts can push via a saved-search webhook action.
- Capabilities
- read · write · webhooks
- Rate limits
- The management REST API throttles through search-concurrency quotas — max concurrent searches per user and role, plus per-CPU historical search limits in limits.conf — rather than a fixed per-request rate; exceeding quota queues or blocks jobs. HEC has per-token and per-instance throughput limits, and Splunk Cloud adds ingestion and API limits on top.
How it works
How to connect Neo4j to Splunk — 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 Neo4j and Splunk with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Neo4j
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Neo4j and Splunk 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 · Neo4j ⇄ SplunkCustomers 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.
Neo4j SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Neo4j and Splunk integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Neo4j and Splunk: authenticate both systems, choose the objects to sync (such as Neo4j's Users & Roles and Nodes), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Splunk: Authentication supports HTTP Basic, a session key from /services/auth/login (Authorization: Splunk <key>), and bearer authentication tokens; the HTTP Event Collector uses its own per-input token. Neo4j: Neo4j uses a property graph model in which nodes and relationships both carry key-value properties, so edges hold data rather than just linking rows. Stacksync's field mapping accounts for these differences between Neo4j and Splunk without custom code.
-
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 Neo4j and Splunk records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Neo4j and Splunk connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Neo4j–Splunk integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Neo4j and Splunk. 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 Splunk: Time-range searches over indexed events (earliest/latest on _time or _indextime); events are immutable once indexed, so incremental extraction advances a time cursor rather than a modified-date CDC feed. Config objects such as saved searches and KV Store are polled; alerts can push via a saved-search webhook action. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 489 integrations available for Neo4j and Splunk.
Popular · 8 of 489
-
Neo4j ⇄ Tableau -
Neo4j ⇄ Adobeanalytics -
Neo4j ⇄ Pendo -
Neo4j ⇄ Treasuredata -
Splunk ⇄ Amazon DynamoDB -
Splunk ⇄ Reltio -
Splunk ⇄ SAP Hana -
Splunk ⇄ Jdbc
No integrations match .
