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Database ⇄ Analytics

AWS Aurora PostgreSQL to Splunk integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL and Splunk

Give Splunk the users, events, and records that live in AWS Aurora PostgreSQL in real time, and sync the cohorts and scores Splunk computes back into AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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 Foreign keys, Replication slots and publications, Databases and schemas, Tables in AWS Aurora PostgreSQL with Fired Alerts, KV Store Collections, Indexes, HTTP Event Collector 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 AWS Aurora PostgreSQL, 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 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
  • 04 Feed operational dashboards from a read replica while the writer handles sync traffic.

Common sync patterns

Filter and grouping dimensions kept fresh

Attributes teams slice by, such as plan, region, or account owner, stay current in Splunk because they sync from AWS Aurora PostgreSQL as they change, instead of going stale after a one-time import.

Where Splunk tracks product events: behavior onto stored records

Signup, usage, and lifecycle events captured in Splunk sync into AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL, where the services that read from the database act on them at query speed without calling the analytics API.

What you can sync between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL objects Splunk objects How this pairing syncs
Replication slots and publications The logical replication objects that power log-based CDC. 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. Replication slots and publications is specific to AWS Aurora PostgreSQL and Dashboards to Splunk — each maps to any object or custom field on the other side.
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. 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. Databases and schemas is specific to AWS Aurora PostgreSQL and Search Results to Splunk — each maps to any object or custom field on the other side.
Tables The core sync unit; rows are matched across systems by primary key. 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 is specific to AWS Aurora PostgreSQL and Saved Searches to Splunk — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. 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. Rows is specific to AWS Aurora PostgreSQL and Fired Alerts to Splunk — each maps to any object or custom field on the other side.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's 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. Columns is specific to AWS Aurora PostgreSQL and KV Store Collections to Splunk — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. 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. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Indexes to Splunk — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL Splunk Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.

Splunk AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL ⇄ Splunk

Connect AWS Aurora PostgreSQL and Splunk for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora PostgreSQL–Splunk connection.

Real-time

Two-way sync

Changes in AWS Aurora PostgreSQL or Splunk instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL or Splunk record.

Observability

Monitoring

Track your AWS Aurora PostgreSQL ⇄ Splunk sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Splunk.

How the AWS Aurora PostgreSQL and Splunk connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
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 AWS Aurora PostgreSQL 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.

  1. 01

    Connect your apps

    Authenticate AWS Aurora PostgreSQL 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    AWS Aurora PostgreSQL connected
    Splunk connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS Aurora PostgreSQL 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · AWS Aurora PostgreSQL ⇄ Splunk
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    AWS Aurora PostgreSQL Splunk
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS Aurora PostgreSQL and Splunk integration FAQ

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.

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→ 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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 424 integrations available for AWS Aurora PostgreSQL and Splunk.

Popular · 8 of 424
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