Real-time
Two-way sync
Changes in Apache Druid or Splunk instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Analytics
Apache Druid to Splunk integration — real-time, two-way sync
Keep Apache Druid 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.
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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Apache Druid and Splunk
Put the same events, users, and metrics on both sides: Splunk and Apache Druid stay current in real time, in both directions.
Splunk is where teams explore, visualize, and report; Apache Druid 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 Users and Roles, Dashboards, Search Results, Saved Searches in Splunk with Tasks, Datasources, Segments, Dimensions in Apache Druid 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 Apache Druid, 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 Sync Druid query results into a warehouse to combine real-time aggregates with historical models.
- 04 Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
Common sync patterns
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.
One number both sides agree on
Metrics and aggregates stay aligned between the two systems, so a figure shown in Splunk matches the Apache Druid table it was built from instead of drifting between refreshes.
Where Apache Druid holds the source tables: live data in the reporting layer
Records maintained in Apache Druid flow into Splunk as they change, so dashboards and reports read current rows rather than an overnight extract.
What you can sync between Apache Druid 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.
| Apache Druid objects | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | 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. | Segments is specific to Apache Druid and HTTP Event Collector to Splunk — each maps to any object or custom field on the other side. | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | 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. | Dimensions is specific to Apache Druid and Users and Roles to Splunk — each maps to any object or custom field on the other side. | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | 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. | Metrics is specific to Apache Druid and Dashboards to Splunk — each maps to any object or custom field on the other side. | |
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | 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. | Ingestion Supervisors is specific to Apache Druid and Search Results to Splunk — each maps to any object or custom field on the other side. | |
| Lookups Key-value mappings joined at query time, refreshable from external systems. | 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. | Lookups is specific to Apache Druid and Saved Searches to Splunk — each maps to any object or custom field on the other side. | |
| Tasks Batch ingestion and compaction jobs monitored during data loads. | 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. | Tasks is specific to Apache Druid and Fired Alerts to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between Apache Druid 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.
Apache Druid Splunk Interval-based propagation
DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.
DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.
Splunk Apache Druid 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 Apache Druid as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
- 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 Apache Druid ⇄ Splunk
Connect Apache Druid and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Druid 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 Apache Druid or Splunk record.
Observability
Monitoring
Track your Apache Druid ⇄ Splunk sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Apache Druid and Splunk.
How the Apache Druid and Splunk connectors work
Apache Druid
- Integration surface
- REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
- Authentication
- Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
- Change detection
- Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
- Capabilities
- read · write
- Rate limits
- No fixed API quotas; query concurrency is bounded by broker and historical node capacity
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 Apache Druid 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 Apache Druid 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.
Apache Druid
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Druid 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 · Apache Druid ⇄ 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.
Apache Druid SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Druid and Splunk integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Apache Druid and Splunk: authenticate both systems, choose the objects to sync (such as Apache Druid's Segments and Dimensions), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Apache Druid: REST API (SQL over HTTP and native JSON queries); JDBC via Avatica. Authentication: Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy. 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.
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Splunk: The KV Store is a MongoDB-backed, app-scoped collection store with full CRUD and batch endpoints (/servicesNS/{owner}/{app}/storage/collections/data/{collection}), so lookup records can be read and written in both directions. Apache Druid: It exposes both a SQL API over HTTP and a native JSON query language, with SQL translated onto native queries. Stacksync's field mapping accounts for these differences between Apache Druid and Splunk without custom code.
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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 Apache Druid 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 Apache Druid and Splunk connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Druid–Splunk integration in-house.
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Yes — Stacksync ships production-grade connectors for both Apache Druid and Splunk. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 412 integrations available for Apache Druid and Splunk.
Popular · 8 of 412
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Apache Druid ⇄ Microsoft Power Bi -
Apache Druid ⇄ Tableau -
Apache Druid ⇄ Adobeanalytics -
Apache Druid ⇄ Pendo -
Splunk ⇄ Snowflake -
Splunk ⇄ BigQuery -
Splunk ⇄ MotherDuck -
Splunk ⇄ Databricks
No integrations match .
