Real-time
Two-way sync
Changes in PostgreSQL or Treasuredata instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Analytics
PostgreSQL to Treasuredata integration — real-time, two-way sync
Keep PostgreSQL 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.
- 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 PostgreSQL and Treasuredata
Give Treasuredata the users, events, and records that live in PostgreSQL in real time, and sync the cohorts and scores Treasuredata computes back into 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. Treasuredata is where people make sense of them, as dashboards, funnels, cohorts, and metrics. Moving the data from PostgreSQL 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 JSONB Columns, Sequences, Custom Types and Enums, Tables in PostgreSQL with Segments, Journeys, Predictive Segments, Scheduled Queries 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 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 Push Predictive Segment propensity scores from TD onto customer records in an operational database or CRM for prioritization and lead routing.
- 02 Write CRM and product-usage records into TD Tables so they become source tables feeding parent-segment unification.
- 03 Consolidate data from several microservice databases into one operational Postgres store
- 04 Feed reporting and BI from a continuously synced Postgres replica instead of scheduled ETL scripts
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 Treasuredata because they sync from PostgreSQL as they change, instead of going stale after a one-time import.
Where Treasuredata tracks product events: behavior onto stored records
Signup, usage, and lifecycle events captured in Treasuredata sync into PostgreSQL as rows, so applications and internal tools can read behavioral data next to the records they already keep.
What you can sync between PostgreSQL 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.
| PostgreSQL objects | Treasuredata objects | How this pairing syncs | |
|---|---|---|---|
| Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. | 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. | |
| Columns Field-level mapping targets; types are mapped to the connected system's field types. | Predictive Segments AI/ML-scored segments; propensity scores read out and written onto customer records in a CRM or database for prioritization. | Columns is specific to PostgreSQL and Predictive Segments to Treasuredata — each maps to any object or custom field on the other side. | |
| Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. | Scheduled Queries Cron-scheduled Presto/Trino (or Hive) jobs that materialize results into result tables; Stacksync reads those materialized tables downstream. | Primary and Unique Keys is specific to PostgreSQL and Scheduled Queries to Treasuredata — each maps to any object or custom field on the other side. | |
| JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. | Query Jobs Ad-hoc Presto/Trino query jobs run asynchronously; results are retrieved from the job result endpoint and fed into downstream systems. | JSONB Columns is specific to PostgreSQL and Query Jobs to Treasuredata — each maps to any object or custom field on the other side. | |
| Sequences Generate surrogate keys for rows created by inbound syncs. | Databases Logical containers for tables; a sync targets one database and maps its tables to warehouse or operational-DB tables. | Sequences is specific to PostgreSQL and Databases to Treasuredata — each maps to any object or custom field on the other side. | |
| Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. | 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. | Custom Types and Enums is specific to PostgreSQL and Master (Parent) Segments to Treasuredata — each maps to any object or custom field on the other side. |
How changes propagate between PostgreSQL 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.
PostgreSQL Treasuredata Sub-second propagation
DetectionChanges in PostgreSQL are captured at the source via change data capture — no polling loop against its API. Logical replication (wal_level = logical) for change data capture via the "Postgres" connector.
DeliveryEach detected change is written to Treasuredata through its API, with automatic retries and rate-limit backoff.
Treasuredata PostgreSQL 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 PostgreSQL as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- PostgreSQL: No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput.
- 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 PostgreSQL ⇄ Treasuredata
Connect PostgreSQL and Treasuredata for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every PostgreSQL–Treasuredata connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever PostgreSQL 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 PostgreSQL or Treasuredata record.
Observability
Monitoring
Track your PostgreSQL ⇄ Treasuredata sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between PostgreSQL and Treasuredata.
How the PostgreSQL and Treasuredata connectors work
PostgreSQL
- Integration surface
- SQL wire protocol (PostgreSQL frontend/backend protocol)
- Authentication
- Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user
- Change detection
- Logical replication (wal_level = logical) for change data capture via the "Postgres" connector; database triggers (TRIGGER grant + stacksync_logging schema) via the trigger-based "Postgres Heroku" connector where
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits; throughput is bounded by connection limits, instance resources, and replication slot throughput
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 PostgreSQL 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.
- 01
Connect your apps
Authenticate PostgreSQL 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.
PostgreSQL
connected
Treasuredata
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the PostgreSQL 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.
objects · PostgreSQL ⇄ TreasuredataCustomers 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.
PostgreSQL TreasuredataCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
PostgreSQL and Treasuredata integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between PostgreSQL and Treasuredata: authenticate both systems, choose the objects to sync (such as PostgreSQL's Tables and Columns), map fields visually, and changes propagate both ways in milliseconds — no code required.
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PostgreSQL: SQL wire protocol (PostgreSQL frontend/backend protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user. Treasuredata: 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). Stacksync manages authentication, retries, and rate limits on both sides.
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Treasuredata: Every TD table requires a `time` column (Unix epoch); it is the primary partition key and the natural incremental cursor for time-based sync. PostgreSQL: INSERT ... ON CONFLICT gives native upsert semantics, which makes inbound syncs idempotent against primary or unique keys. Stacksync's field mapping accounts for these differences between PostgreSQL and Treasuredata 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 PostgreSQL and Treasuredata 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 PostgreSQL and Treasuredata connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom PostgreSQL–Treasuredata integration in-house.
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Yes — Stacksync ships production-grade connectors for both PostgreSQL and Treasuredata. 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
Every pair below is a real-time, two-way sync. Search all 419 integrations available for PostgreSQL and Treasuredata.
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