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Data warehouse ⇄ Analytics

AWS S3 to Treasuredata integration — real-time, two-way sync

Keep AWS S3 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 AWS S3 and Treasuredata

Put the same events, users, and metrics on both sides: Treasuredata and AWS S3 stay current in real time, in both directions.

Treasuredata is where teams explore, visualize, and report; AWS S3 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 Predictive Segments, Scheduled Queries, Query Jobs, Databases in Treasuredata with Prefixes, Object Metadata, Object Versions, Event Notifications in AWS S3 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 AWS S3, every copy stays consistent.

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 Export synced operational data to S3 as files feeding a data lake or downstream batch jobs.
  • 04 Trigger incremental sync runs from S3 event notifications when new files land in a prefix.

Common sync patterns

One number both sides agree on

Metrics and aggregates stay aligned between the two systems, so a figure shown in Treasuredata matches the AWS S3 table it was built from instead of drifting between refreshes.

Where AWS S3 holds the source tables: live data in the reporting layer

Records maintained in AWS S3 flow into Treasuredata as they change, so dashboards and reports read current rows rather than an overnight extract.

Where Treasuredata produces segments or scores: results back to the warehouse

Cohorts, segments, and computed metrics defined in Treasuredata write to AWS S3 as tables the rest of the stack can query and join.

What you can sync between AWS S3 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.

AWS S3 objects Treasuredata objects How this pairing syncs
Buckets Top-level containers a sync targets; region and policy are set at this level. Databases Logical containers for tables; a sync targets one database and maps its tables to warehouse or operational-DB tables. Buckets is specific to AWS S3 and Databases to Treasuredata — each maps to any object or custom field on the other side.
Objects The stored files (CSV, JSON, Parquet); syncs read them as datasets or write exports into them. 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. Objects is specific to AWS S3 and Tables to Treasuredata — each maps to any object or custom field on the other side.
Prefixes Key-name paths used to partition synced datasets, since S3 has no real directories. Master (Parent) Segments Unified customer profiles assembled from multiple source tables in Audience Studio; read out to push enriched attributes onto CRM or warehouse records. Prefixes is specific to AWS S3 and Master (Parent) Segments to Treasuredata — each maps to any object or custom field on the other side.
Object Metadata System and user-defined metadata read alongside object contents. Segments Campaign subsets of a parent segment; membership read out to activate audiences in downstream systems, or audience flags written back onto records. Object Metadata is specific to AWS S3 and Segments to Treasuredata — each maps to any object or custom field on the other side.
Object Versions Prior copies retained when versioning is enabled, relevant for reprocessing. Journeys Timeline-based event sequences in Audience Studio; stage and membership read out for reporting and cross-system activation. Object Versions is specific to AWS S3 and Journeys to Treasuredata — each maps to any object or custom field on the other side.
Event Notifications Notifications on object creation or deletion that trigger incremental processing. Predictive Segments AI/ML-scored segments; propensity scores read out and written onto customer records in a CRM or database for prioritization. Event Notifications is specific to AWS S3 and Predictive Segments to Treasuredata — each maps to any object or custom field on the other side.

How changes propagate between AWS S3 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.

AWS S3 Treasuredata Sub-second propagation

DetectionAWS S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge.

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

Treasuredata AWS S3 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 written to AWS S3 through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • AWS S3: Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes.
  • 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 AWS S3 ⇄ Treasuredata

Connect AWS S3 and Treasuredata for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS S3–Treasuredata connection.

Real-time

Two-way sync

Changes in AWS S3 or Treasuredata instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS S3 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 AWS S3 or Treasuredata record.

Observability

Monitoring

Track your AWS S3 ⇄ Treasuredata sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS S3 and Treasuredata.

How the AWS S3 and Treasuredata connectors work

AWS S3

Integration surface
REST API (the S3 API), accessed directly or through AWS SDKs
Authentication
AWS IAM credentials with SigV4 signing; commonly a role scoped to specific buckets and prefixes
Change detection
S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge; list-based polling as a fallback
Capabilities
read · write · webhooks
Rate limits
Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes

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 AWS S3 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 AWS S3 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
    AWS S3 connected
    Treasuredata connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS S3 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 · AWS S3 ⇄ 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
    AWS S3 Treasuredata
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS S3 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.

Learn more about security
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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:

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 417 integrations available for AWS S3 and Treasuredata.

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