Real-time
Two-way sync
Changes in AWS Aurora MySQL or Splunk instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Analytics
AWS Aurora MySQL to Splunk integration — real-time, two-way sync
Keep AWS Aurora MySQL 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
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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 MySQL and Splunk
Give Splunk the users, events, and records that live in AWS Aurora MySQL in real time, and sync the cohorts and scores Splunk computes back into AWS Aurora MySQL 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 MySQL 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 Rows, Columns, Primary keys and indexes, Views in AWS Aurora MySQL with Indexes, HTTP Event Collector, Users and Roles, Dashboards 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 MySQL, 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 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 Stream row changes from Aurora into SaaS tools via binlog CDC instead of scheduled batch exports.
- 04 Sync a production Aurora cluster with an analytics database while filtering out sensitive columns.
Common sync patterns
One version of each user or account
A user, account, or record corrected in either system updates the other, so the identity your reports group by matches the identity your database stores.
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 MySQL 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 MySQL as rows, so applications and internal tools can read behavioral data next to the records they already keep.
What you can sync between AWS Aurora MySQL 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 MySQL objects | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | 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 (schemas) is specific to AWS Aurora MySQL and Search Results to Splunk — each maps to any object or custom field on the other side. | |
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | 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 MySQL and Saved Searches to Splunk — each maps to any object or custom field on the other side. | |
| Rows Inserted, updated, and deleted individually or in bulk during two-way 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 MySQL and Fired Alerts to Splunk — each maps to any object or custom field on the other side. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | 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 MySQL and KV Store Collections to Splunk — each maps to any object or custom field on the other side. | |
| Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | 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 indexes is specific to AWS Aurora MySQL and Indexes to Splunk — each maps to any object or custom field on the other side. | |
| Views Can serve as read-only sync sources for derived or filtered datasets. | 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 AWS Aurora MySQL and HTTP Event Collector to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between AWS Aurora MySQL 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 MySQL Splunk Sub-second propagation
DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.
DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.
Splunk AWS Aurora MySQL 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 MySQL 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 MySQL ⇄ Splunk
Connect AWS Aurora MySQL and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever AWS Aurora MySQL 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 MySQL or Splunk record.
Observability
Monitoring
Track your AWS Aurora MySQL ⇄ 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 MySQL and Splunk.
How the AWS Aurora MySQL and Splunk connectors work
AWS Aurora MySQL
- Integration surface
- SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC
- Authentication
- Database credentials, optionally AWS IAM database authentication, over TLS
- Change detection
- Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns 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 MySQL 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 AWS Aurora MySQL 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.
AWS Aurora MySQL
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the AWS Aurora MySQL 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 · AWS Aurora MySQL ⇄ 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.
AWS Aurora MySQL SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
AWS Aurora MySQL and Splunk integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between AWS Aurora MySQL and Splunk: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Databases (schemas) and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Splunk: Authentication supports HTTP Basic, a session key from /services/auth/login (Authorization: Splunk <key>), and bearer authentication tokens; the HTTP Event Collector uses its own per-input token. AWS Aurora MySQL: Aurora MySQL is wire-compatible with MySQL, so any standard MySQL driver, ORM, or CDC tooling works without modification. Stacksync's field mapping accounts for these differences between AWS Aurora MySQL 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 AWS Aurora MySQL 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 AWS Aurora MySQL and Splunk connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora MySQL–Splunk integration in-house.
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Yes — Stacksync ships production-grade connectors for both AWS Aurora MySQL 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 AWS Aurora MySQL: Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback. 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.
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 422 integrations available for AWS Aurora MySQL and Splunk.
Popular · 7 of 422
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AWS Aurora MySQL ⇄ Mixpanel -
AWS Aurora MySQL ⇄ Microsoft Power Bi -
AWS Aurora MySQL ⇄ Tableau -
Splunk ⇄ Supabase -
Splunk ⇄ MySQL -
Splunk ⇄ MariaDB -
Splunk ⇄ SQL Server
No integrations match .
