Real-time
Two-way sync
Changes in ClickHouse or Splunk instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Analytics
ClickHouse to Splunk integration — real-time, two-way sync
Keep ClickHouse 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 ClickHouse and Splunk
Put the same events, users, and metrics on both sides: Splunk and ClickHouse stay current in real time, in both directions.
Splunk is where teams explore, visualize, and report; ClickHouse is the store of record that holds the raw tables and full history behind those views. The two overlap wherever the same events, users, and metrics matter to both, and when the bridge between them is a nightly export or a hand-built extract, dashboards lag the warehouse and analysts spend the morning arguing over whose number is right.
Stacksync syncs Saved Searches, Fired Alerts, KV Store Collections, Indexes in Splunk with Databases, Views, Materialized views, Distributed tables in ClickHouse field by field, in real time, and in both directions. You decide which system owns which fields, and Stacksync resolves conflicts by rules you set. Whether the flow is warehouse tables feeding live reports or captured events and segments landing back in ClickHouse, every copy stays consistent.
Common use cases
- 01 Sync fired-alert history and saved-search definitions into Postgres so security and reliability teams query alert trends and detection coverage in SQL.
- 02 Ingest application, CRM, or database records into Splunk via the HTTP Event Collector so operational data lands alongside logs for correlation and dashboards.
- 03 Consolidate logs and business records from multiple sources into MergeTree tables for retention and reporting.
- 04 Land product event data alongside synced CRM accounts so analysts join usage and revenue in one place.
Common sync patterns
Where Splunk produces segments or scores: results back to the warehouse
Cohorts, segments, and computed metrics defined in Splunk write to ClickHouse as tables the rest of the stack can query and join.
Shared user and account keys
Users and accounts tracked in Splunk line up with the customer or user rows in ClickHouse on a stable key, so both sides count the same population.
Corrections propagate instead of reloading
When a record is fixed or backfilled on one side, the change reaches the other without a full reload, keeping history consistent across both.
What you can sync between ClickHouse 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.
| ClickHouse objects | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Distributed tables Query-routing tables over cluster shards in self-managed deployments. | 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 ClickHouse and Dashboards to Splunk — each maps to any object or custom field on the other side. | |
| Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. | 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. | Dictionaries is specific to ClickHouse and Search Results to Splunk — each maps to any object or custom field on the other side. | |
| Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. | 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. | Tables (MergeTree family) is specific to ClickHouse and Saved Searches to Splunk — each maps to any object or custom field on the other side. | |
| Databases Namespaces that group tables and scope permissions for sync users. | 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. | Databases is specific to ClickHouse and Fired Alerts to Splunk — each maps to any object or custom field on the other side. | |
| Views Saved queries used as curated, read-only sync sources. | 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. | Views is specific to ClickHouse and KV Store Collections to Splunk — each maps to any object or custom field on the other side. | |
| Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. | 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. | Materialized views is specific to ClickHouse and Indexes to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between ClickHouse 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.
ClickHouse Splunk Interval-based propagation
DetectionStacksync polls ClickHouse for changes on an incremental schedule, reading only records changed since the previous pass. No log-based CDC for consumers.
DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.
Splunk ClickHouse 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 ClickHouse 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 ClickHouse ⇄ Splunk
Connect ClickHouse and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every ClickHouse–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever ClickHouse 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 ClickHouse or Splunk record.
Observability
Monitoring
Track your ClickHouse ⇄ Splunk sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between ClickHouse and Splunk.
How the ClickHouse and Splunk connectors work
ClickHouse
- Integration surface
- Native TCP protocol and HTTP interface; standard SQL dialect, with MySQL and PostgreSQL wire compatibility available
- Authentication
- Database credentials (username/password); ClickHouse Cloud issues per-service credentials over TLS
- Change detection
- No log-based CDC for consumers; incremental reads use polling on monotonic columns, and ClickHouse is usually the destination rather than the source
- Capabilities
- read · write
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 ClickHouse 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 ClickHouse 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.
ClickHouse
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the ClickHouse 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 · ClickHouse ⇄ 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.
ClickHouse SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
ClickHouse and Splunk integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between ClickHouse and Splunk: authenticate both systems, choose the objects to sync (such as ClickHouse's Distributed tables and Dictionaries), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Common patterns for ClickHouse and Splunk: Where Splunk produces segments or scores: results back to the warehouse; Shared user and account keys; Corrections propagate instead of reloading. Cohorts, segments, and computed metrics defined in Splunk write to ClickHouse as tables the rest of the stack can query and join.
-
ClickHouse: Native TCP protocol and HTTP interface; standard SQL dialect, with MySQL and PostgreSQL wire compatibility available. Authentication: Database credentials (username/password); ClickHouse Cloud issues per-service credentials over TLS. Splunk: 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). Stacksync manages authentication, retries, and rate limits on both sides.
-
Splunk: The REST API is governed by search-concurrency quotas (per-user/role and per-CPU historical search limits in limits.conf) rather than a fixed request rate; HEC and Splunk Cloud add throughput and ingestion limits. ClickHouse: It exposes both a native TCP protocol and an HTTP interface, and can additionally speak MySQL and PostgreSQL wire protocols for compatibility with existing drivers. Stacksync's field mapping accounts for these differences between ClickHouse 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 ClickHouse and Splunk records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed ClickHouse and Splunk connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom ClickHouse–Splunk integration in-house.
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 512 integrations available for ClickHouse and Splunk.
Popular · 8 of 512
-
ClickHouse ⇄ Pendo -
ClickHouse ⇄ Treasuredata -
ClickHouse ⇄ Mixpanel -
ClickHouse ⇄ Microsoft Power Bi -
Splunk ⇄ Vertica -
Splunk ⇄ Yellowbrick -
Splunk ⇄ Snowflake -
Splunk ⇄ BigQuery
No integrations match .
