Two-way sync
Changes in PostgreSQL or Snowflake instantly reflect in both systems. No stale data, no manual imports.
Keep PostgreSQL and Snowflake in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want PostgreSQL's rows in Snowflake, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in PostgreSQL where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in PostgreSQL sync into Snowflake in real time, and result tables in Snowflake sync back into PostgreSQL, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Snowflake and keep PostgreSQL focused on its operational workload.
Rows from PostgreSQL land in Snowflake as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Snowflake sync into PostgreSQL, where whatever reads from that database gets them without querying the warehouse.
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 | Snowflake objects | |
|---|---|---|
| Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. | Tasks Scheduled SQL used to transform synced data after it lands. | |
| JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. | VARIANT Columns Semi-structured JSON payloads stored alongside relational columns. | |
| Sequences Generate surrogate keys for rows created by inbound syncs. | Virtual Warehouses The compute a sync's queries run on, sized independently of storage. | |
| Custom Types and Enums Constrain synced values to a fixed set, mirroring picklist fields. | Databases Top-level containers that scope which data a sync can touch. | |
| Tables The primary sync target; rows map one-to-one to records in connected SaaS systems. | Schemas Namespaces within a database used to organize synced tables. | |
| Views Read-side projections used to expose joined or filtered data to a sync. | Tables The main landing and activation target for synced records. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every PostgreSQL–Snowflake connection.
Changes in PostgreSQL or Snowflake instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever PostgreSQL or Snowflake data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single PostgreSQL or Snowflake record.
Track your PostgreSQL ⇄ Snowflake sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between PostgreSQL and Snowflake.
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.
Authenticate PostgreSQL and Snowflake with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the PostgreSQL and Snowflake 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between PostgreSQL and Snowflake: authenticate both systems, choose the objects to sync (such as PostgreSQL's Primary and Unique Keys and JSONB Columns), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both PostgreSQL and Snowflake. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on PostgreSQL: 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. On Snowflake: Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Snowflake side: Stages, Tasks, VARIANT Columns, Virtual Warehouses, plus custom fields where Snowflake exposes them. On the PostgreSQL side: Columns, Primary and Unique Keys, JSONB Columns, Sequences. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for PostgreSQL and Snowflake: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Snowflake and keep PostgreSQL focused on its operational workload.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for PostgreSQL and Snowflake.