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Database ⇄ Analytics

Amazon DynamoDB to Treasuredata integration — real-time, two-way sync

Keep Amazon DynamoDB and Treasuredata 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 Treasuredata

Give Treasuredata the users, events, and records that live in Amazon DynamoDB in real time, and sync the cohorts and scores Treasuredata 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. Treasuredata is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from Amazon DynamoDB into Treasuredata 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 Global Tables, Time to Live (TTL), Tables, Items in Amazon DynamoDB with Databases, Tables, Master (Parent) Segments, Segments in Treasuredata in real time and in both directions. Operational rows flow into Treasuredata as they change, so dashboards read current data with no pipeline to maintain, and the segments, cohorts, or scores Treasuredata 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 Write CRM and product-usage records into TD Tables so they become source tables feeding parent-segment unification.
  • 02 Push Predictive Segment propensity scores from TD onto customer records in an operational database or CRM for prioritization and lead routing.
  • 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 Treasuredata tracks product events: behavior onto stored records

Signup, usage, and lifecycle events captured in Treasuredata sync into Amazon DynamoDB as rows, so applications and internal tools can read behavioral data next to the records they already keep.

Where Treasuredata builds cohorts or scores: results your services can read

Segments, cohorts, or scores computed in Treasuredata 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 Treasuredata 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 Treasuredata

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 Treasuredata objects How this pairing syncs
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. Tables Columnar log tables in TD's Plazma storage; every row carries a mandatory `time` column (Unix epoch) that Stacksync uses as the incremental watermark and partition key. Synced two-way with warehouse or database tables. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
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. Segments Campaign subsets of a parent segment; membership read out to activate audiences in downstream systems, or audience flags written back onto records. Global Tables is specific to Amazon DynamoDB and Segments to Treasuredata — 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. Journeys Timeline-based event sequences in Audience Studio; stage and membership read out for reporting and cross-system activation. Time to Live (TTL) is specific to Amazon DynamoDB and Journeys to Treasuredata — 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. Predictive Segments AI/ML-scored segments; propensity scores read out and written onto customer records in a CRM or database for prioritization. Items is specific to Amazon DynamoDB and Predictive Segments to Treasuredata — each maps to any object or custom field on the other side.
Global secondary indexes (GSIs) Alternate key projections that let you Query by non-key attributes without a full table Scan; read-only views maintained automatically by DynamoDB. Scheduled Queries Cron-scheduled Presto/Trino (or Hive) jobs that materialize results into result tables; Stacksync reads those materialized tables downstream. Global secondary indexes (GSIs) is specific to Amazon DynamoDB and Scheduled Queries to Treasuredata — each maps to any object or custom field on the other side.
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. Query Jobs Ad-hoc Presto/Trino query jobs run asynchronously; results are retrieved from the job result endpoint and fed into downstream systems. Local secondary indexes (LSIs) is specific to Amazon DynamoDB and Query Jobs to Treasuredata — each maps to any object or custom field on the other side.

How changes propagate between Amazon DynamoDB and Treasuredata

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 Treasuredata 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 Treasuredata through its API, with automatic retries and rate-limit backoff.

Treasuredata Amazon DynamoDB Interval-based propagation

DetectionStacksync polls Treasuredata for changes on an incremental schedule, reading only records changed since the previous pass. Polling on the mandatory `time` column (Unix-epoch partition key) or an updated-at column.

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.
  • Treasuredata: TD does not publish a fixed request-per-second cap; query throughput is bounded by the account's compute resource pool and large reads/exports run as asynchronous jobs.
What ships with Amazon DynamoDB ⇄ Treasuredata

Connect Amazon DynamoDB and Treasuredata for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon DynamoDB–Treasuredata connection.

Real-time

Two-way sync

Changes in Amazon DynamoDB or Treasuredata instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon DynamoDB or Treasuredata 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 Treasuredata record.

Observability

Monitoring

Track your Amazon DynamoDB ⇄ Treasuredata 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 Treasuredata.

How the Amazon DynamoDB and Treasuredata 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.

Treasuredata

Integration surface
TD API v3 (REST) for databases, tables, and jobs, plus the Audience API (REST) for CDP segments and journeys
Authentication
API key sent as an `Authorization: TD1 <api_key>` header (per-user or account key from the TD Console); requests go to the region-specific endpoint (e.g. api.treasuredata.com for US, with separate EU and Tokyo endpoints)
Change detection
Polling on the mandatory `time` column (Unix-epoch partition key) or an updated-at column; TD stores append-oriented columnar data with no per-row CDC stream, so incremental syncs query for rows past a stored watermark
Capabilities
read · write
Rate limits
TD does not publish a fixed request-per-second cap; query throughput is bounded by the account's compute resource pool and large reads/exports run as asynchronous jobs
How it works

How to connect Amazon DynamoDB to Treasuredata — 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 Amazon DynamoDB and Treasuredata 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
    Amazon DynamoDB connected
    Treasuredata connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon DynamoDB and Treasuredata 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 · Amazon DynamoDB ⇄ Treasuredata
    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
    Amazon DynamoDB Treasuredata
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon DynamoDB and Treasuredata 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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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 412 integrations available for Amazon DynamoDB and Treasuredata.

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