Real-time
Two-way sync
Changes in Materialize or Splunk instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Analytics
Materialize to Splunk integration — real-time, two-way sync
Keep Materialize 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 Materialize and Splunk
Put the same events, users, and metrics on both sides: Splunk and Materialize stay current in real time, in both directions.
Splunk is where teams explore, visualize, and report; Materialize 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 Tables, Sources, Materialized Views, Sinks in Materialize 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 Materialize, every copy stays consistent.
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 Bridge streaming sources and non-streaming destinations by materializing joins across both.
- 04 Sync operational CRM or ERP data into Materialize so real-time views stay current without batch loads.
Common sync patterns
Where Splunk produces segments or scores: results back to the warehouse
Cohorts, segments, and computed metrics defined in Splunk write to Materialize 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 Materialize 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 Materialize 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.
| Materialize objects | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Indexes In-memory arrangements that make view reads fast for serving workloads. | 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. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Sources Ingestion points (Kafka, Postgres CDC, MySQL CDC, webhook) that feed external data into Materialize. | 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. | Sources is specific to Materialize and HTTP Event Collector to Splunk — each maps to any object or custom field on the other side. | |
| Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. | 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. | Materialized Views is specific to Materialize and Users and Roles to Splunk — each maps to any object or custom field on the other side. | |
| Sinks Outbound connections that emit view changes to Kafka topics. | 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. | Sinks is specific to Materialize and Dashboards to Splunk — each maps to any object or custom field on the other side. | |
| Clusters Compute pools that isolate ingestion, view maintenance, and serving. | 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. | Clusters is specific to Materialize and Search Results to Splunk — each maps to any object or custom field on the other side. | |
| Connections & Secrets Stored credentials and endpoints used by sources and sinks. | 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. | Connections & Secrets is specific to Materialize and Saved Searches to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between Materialize 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.
Materialize Splunk Sub-second propagation
DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.
DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.
Splunk Materialize 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 Materialize 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 Materialize ⇄ Splunk
Connect Materialize and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Materialize–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Materialize 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 Materialize or Splunk record.
Observability
Monitoring
Track your Materialize ⇄ Splunk sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Materialize and Splunk.
How the Materialize and Splunk connectors work
Materialize
- Integration surface
- PostgreSQL wire protocol (SQL)
- Authentication
- Database credentials (username/password; app passwords in the managed cloud service)
- Change detection
- SUBSCRIBE queries stream row-level changes of any view or table to the client
- 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 Materialize 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 Materialize 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.
Materialize
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Materialize 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 · Materialize ⇄ 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.
Materialize SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Materialize and Splunk integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Materialize and Splunk: authenticate both systems, choose the objects to sync (such as Materialize's Indexes and Sources), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Materialize 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 Materialize: SUBSCRIBE queries stream row-level changes of any view or table to the client. 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: Users and Roles, Dashboards, Search Results, Saved Searches, plus custom fields where Splunk exposes them. On the Materialize side: Tables, Sources, Materialized Views, Sinks. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Materialize 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 Materialize as tables the rest of the stack can query and join.
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
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