Real-time
Two-way sync
Changes in Amazon DynamoDB or Splunk instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Analytics
Amazon DynamoDB to Splunk integration — real-time, two-way sync
Keep Amazon DynamoDB 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 Amazon DynamoDB and Splunk
Give Splunk the users, events, and records that live in Amazon DynamoDB in real time, and sync the cohorts and scores Splunk computes back into Amazon DynamoDB 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 Amazon DynamoDB 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 Tables, Items, Global secondary indexes (GSIs), Local secondary indexes (LSIs) in Amazon DynamoDB with Search Results, Saved Searches, Fired Alerts, KV Store Collections 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 Amazon DynamoDB, 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 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 Mirror a high-write DynamoDB table into a relational database so teams can join NoSQL application data against relational tables for reporting.
- 04 Use DynamoDB Streams as a change-data-capture source to push item INSERT, MODIFY, and REMOVE events into a CRM, search index, or operational database in near-real-time.
Common sync patterns
Where Splunk tracks product events: behavior onto stored records
Signup, usage, and lifecycle events captured in Splunk sync into Amazon DynamoDB 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 Amazon DynamoDB, where the services that read from the database act on them at query speed without calling the analytics API.
Analytics on live operational data, minus the pipeline
The users, events, orders, and records stored in Amazon DynamoDB land in Splunk as they change, so dashboards, funnels, and metrics run on current data instead of last night's extract.
What you can sync between Amazon DynamoDB 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.
| Amazon DynamoDB objects | Splunk objects | How this pairing syncs | |
|---|---|---|---|
| Local secondary indexes (LSIs) Extra sort keys within the same partition key, defined at table creation; queried like the base table for alternate access patterns. | 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. | Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Indexes to Splunk — each maps to any object or custom field on the other side. | |
| DynamoDB Streams Ordered item-level change records (INSERT, MODIFY, REMOVE) with old/new image views and 24-hour retention; the native change-data-capture source Stacksync reads for near-real-time sync. | 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. | DynamoDB Streams is specific to Amazon DynamoDB and HTTP Event Collector to Splunk — each maps to any object or custom field on the other side. | |
| Global Tables Multi-region, active-active replicas of a table kept in sync by DynamoDB; each region is read and written locally with last-writer-wins conflict resolution. | 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. | Global Tables is specific to Amazon DynamoDB and Users and Roles to Splunk — each maps to any object or custom field on the other side. | |
| Time to Live (TTL) Per-item expiry timestamps; DynamoDB deletes expired items in the background and emits a Streams REMOVE record for each deletion. | 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. | Time to Live (TTL) is specific to Amazon DynamoDB and Dashboards to Splunk — each maps to any object or custom field on the other side. | |
| Tables Top-level containers, each with a partition key and optional sort key; Stacksync syncs a table as a stream of items with full read and write via PutItem, UpdateItem, and DeleteItem. | 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. | Tables is specific to Amazon DynamoDB and Search Results to Splunk — each maps to any object or custom field on the other side. | |
| Items Individual schemaless records (attributes up to 400 KB each); read with GetItem, Query, and Scan and written with PutItem or BatchWriteItem, so write is supported here. | 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. | Items is specific to Amazon DynamoDB and Saved Searches to Splunk — each maps to any object or custom field on the other side. |
How changes propagate between Amazon DynamoDB 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.
Amazon DynamoDB Splunk Sub-second propagation
DetectionChanges in Amazon DynamoDB are captured at the source via change data capture — no polling loop against its API. DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views.
DeliveryEach detected change is written to Splunk through its API, with automatic retries and rate-limit backoff.
Splunk Amazon DynamoDB 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 Amazon DynamoDB as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Amazon DynamoDB: Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.
- 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 Amazon DynamoDB ⇄ Splunk
Connect Amazon DynamoDB and Splunk for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon DynamoDB–Splunk connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Amazon DynamoDB 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 Amazon DynamoDB or Splunk record.
Observability
Monitoring
Track your Amazon DynamoDB ⇄ Splunk sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Amazon DynamoDB and Splunk.
How the Amazon DynamoDB and Splunk connectors work
Amazon DynamoDB
- Integration surface
- AWS SDK / low-level HTTPS JSON API at dynamodb.<region>.amazonaws.com (PutItem, GetItem, UpdateItem, DeleteItem, Query, Scan, BatchWriteItem, TransactWriteItems), plus PartiQL (ExecuteStatement) for SQL-style access and DynamoDB Streams for change capture.
- Authentication
- AWS Signature Version 4 (SigV4) signed requests using an IAM access key ID and secret key, or temporary STS credentials from an assumed IAM role; IAM policies scope access down to table and item level.
- Change detection
- DynamoDB Streams emit ordered item-level change records (INSERT, MODIFY, REMOVE) with KEYS_ONLY, NEW_IMAGE, OLD_IMAGE, or NEW_AND_OLD_IMAGES views and 24-hour retention, read via shard iterators (or Kinesis Data Streams for longer retention). No native HTTP webhooks.
- Capabilities
- read · write · CDC
- Rate limits
- Throughput is metered in read/write capacity units (provisioned or on-demand): 1 WCU = one 1 KB write per second, 1 RCU = one strongly-consistent 4 KB read per second. Exceeding capacity or the ~3,000 RCU / 1,000 WCU per-partition ceiling returns ProvisionedThroughputExceededException with throttling.
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 Amazon DynamoDB 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 Amazon DynamoDB 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.
Amazon DynamoDB
connected
Splunk
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Amazon DynamoDB 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 · Amazon DynamoDB ⇄ 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.
Amazon DynamoDB SplunkCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Amazon DynamoDB and Splunk integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Amazon DynamoDB and Splunk: authenticate both systems, choose the objects to sync (such as Amazon DynamoDB's Local secondary indexes (LSIs) and DynamoDB Streams), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Amazon DynamoDB: AWS SDK / low-level HTTPS JSON API at dynamodb.<region>.amazonaws.com (PutItem, GetItem, UpdateItem, DeleteItem, Query, Scan, BatchWriteItem, TransactWriteItems), plus PartiQL (ExecuteStatement) for SQL-style access and DynamoDB Streams for change capture. Authentication: AWS Signature Version 4 (SigV4) signed requests using an IAM access key ID and secret key, or temporary STS credentials from an assumed IAM role; IAM policies scope access down to table and item level. 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. Amazon DynamoDB: A single item can be at most 400 KB. BatchWriteItem handles up to 25 items or 16 MB per call and BatchGetItem up to 100 items or 16 MB, so large syncs are chunked into batches. Stacksync's field mapping accounts for these differences between Amazon DynamoDB 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 Amazon DynamoDB 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 Amazon DynamoDB and Splunk connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Amazon DynamoDB–Splunk integration in-house.
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Yes — Stacksync ships production-grade connectors for both Amazon DynamoDB 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
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