Real-time
Two-way sync
Changes in Citus or Splunk instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Analytics
Citus to Splunk integration — real-time, two-way sync
Keep Citus 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
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Citus and Splunk
Give Splunk the users, events, and records that live in Citus in real time, and sync the cohorts and scores Splunk computes back into Citus 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 Citus 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 Views, Sequences, Distributed tables, Reference tables in Citus 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 Citus, 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 Read and write KV Store collections to keep Splunk lookups — asset inventories, allow/deny lists, enrichment tables — in sync with an external source of truth in both directions.
- 02 Provision and update Saved Searches, alerts, and Dashboards from a Git-backed config repository so detections and reports stay versioned and consistent across search heads.
- 03 Write CRM or billing records into reference tables so distributed queries can join operational context locally on every node.
- 04 Use a Citus cluster as the scalable operational store behind a customer-facing app while syncing summaries back to internal tools.
Common sync patterns
Where Splunk tracks product events: behavior onto stored records
Signup, usage, and lifecycle events captured in Splunk sync into Citus as rows, so applications and internal tools can read behavioral data next to the records they already keep.
Where Splunk builds cohorts or scores: results your services can read
Segments, cohorts, or scores computed in Splunk sync back into Citus, 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 Citus land in Splunk as they change, so dashboards, funnels, and metrics run on current data instead of last night's extract.
What you can sync between Citus 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.
| Citus objects | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Local tables Coordinator-only tables that behave exactly like standard PostgreSQL tables. | 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. | Local tables is specific to Citus and KV Store Collections to Splunk — each maps to any object or custom field on the other side. | |
| Schemas Standard Postgres namespaces used to scope what a sync user can read and write. | 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. | Schemas is specific to Citus and Indexes to Splunk — each maps to any object or custom field on the other side. | |
| Views Curated projections over distributed data, often used as read-only sync sources. | 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. | Views is specific to Citus and HTTP Event Collector to Splunk — each maps to any object or custom field on the other side. | |
| Sequences Key generators that matter when external writes must not collide with application inserts. | Users and Roles Accounts at /services/authentication/users and role/capability definitions at /services/authorization/roles, with full CRUD; exported for access reviews or provisioned from an identity source of truth. | Sequences is specific to Citus and Users and Roles to Splunk — each maps to any object or custom field on the other side. | |
| Distributed tables Tables sharded across worker nodes by a distribution column; the main sync target for large datasets. | Dashboards Simple XML dashboard and view definitions at /servicesNS/{owner}/{app}/data/ui/views; exported for backup and audit, or created and updated programmatically from version control. | Distributed tables is specific to Citus and Dashboards to Splunk — each maps to any object or custom field on the other side. | |
| Reference tables Small lookup tables replicated to every node, synced like ordinary Postgres tables. | 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. | Reference tables is specific to Citus and Search Results to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between Citus 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.
Citus Splunk Sub-second propagation
DetectionChanges in Citus are captured at the source via change data capture — no polling loop against its API. PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres.
DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.
Splunk Citus 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 applied to Citus as a row-level write, with types converted between the two schemas.
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 Citus ⇄ Splunk
Connect Citus and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Citus–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Citus 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 Citus or Splunk record.
Observability
Monitoring
Track your Citus ⇄ Splunk sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Citus and Splunk.
How the Citus and Splunk connectors work
Citus
- Integration surface
- PostgreSQL wire protocol; any standard Postgres driver connects to the coordinator node
- Authentication
- Database credentials (standard PostgreSQL authentication; managed deployments add cloud IAM options)
- Change detection
- PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres
- 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 Citus 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 Citus 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.
Citus
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Citus 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 · Citus ⇄ 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.
Citus SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Citus and Splunk integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Citus and Splunk: authenticate both systems, choose the objects to sync (such as Citus's Local tables and Schemas), 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 Citus and Splunk 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 Citus and Splunk connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Citus–Splunk integration in-house.
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Yes — Stacksync ships production-grade connectors for both Citus and Splunk. 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 Citus: PostgreSQL logical decoding / CDC, with caveats: changes to distributed tables occur on worker shards, so CDC setup differs from single-node Postgres. 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.
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On the Splunk side: Dashboards, Search Results, Saved Searches, Fired Alerts, plus custom fields where Splunk exposes them. On the Citus side: Views, Sequences, Distributed tables, Reference tables. 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 404 integrations available for Citus and Splunk.
Popular · 7 of 404
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Citus ⇄ Pendo -
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Splunk ⇄ Oracle DB -
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Splunk ⇄ Redis Enterprise -
Splunk ⇄ SAP ASE (Sybase)
No integrations match .
