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Data warehouse ⇄ Database

Snowflake to Supabase integration — real-time, two-way sync

Keep Snowflake and Supabase 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 Snowflake and Supabase

Connect Supabase and Snowflake with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Supabase'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 Supabase where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Supabase sync into Snowflake in real time, and result tables in Snowflake sync back into Supabase, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Push product usage aggregates from Snowflake into sales and success tools for account prioritization
  • 02 Feed finance reconciliation models from ERP data landed in Snowflake on a continuous basis
  • 03 Consolidate Supabase project data into a warehouse for analytics while keeping the app database as the system of record
  • 04 Sync application tables in Supabase with the CRM two-way so new signups appear as contacts and sales edits flow back to the app

Common sync patterns

Serve warehouse results at database speed

Aggregates or model outputs computed in Snowflake sync into Supabase, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in Snowflake and keep Supabase focused on its operational workload.

What you can sync between Snowflake and Supabase

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.

Snowflake objects Supabase objects How this pairing syncs
Schemas Namespaces within a database used to organize synced tables. Schemas Namespaces (public and custom) that scope sync access. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. Custom fields on either side are included in the mapping.
Tables The main landing and activation target for synced records. Tables Standard Postgres tables; the primary two-way sync target. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Modeled projections used as the source side of outbound syncs. Views Read-side projections exposed to outbound syncs. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Tasks Scheduled SQL used to transform synced data after it lands. auth.users Managed authentication users, often mirrored into CRM or support systems. Tasks is specific to Snowflake and auth.users to Supabase — each maps to any object or custom field on the other side.
VARIANT Columns Semi-structured JSON payloads stored alongside relational columns. Row Level Security Policies Row-level access rules that govern what the REST layer exposes. VARIANT Columns is specific to Snowflake and Row Level Security Policies to Supabase — each maps to any object or custom field on the other side.
Virtual Warehouses The compute a sync's queries run on, sized independently of storage. JSONB Columns Semi-structured payloads such as event properties or nested objects. Virtual Warehouses is specific to Snowflake and JSONB Columns to Supabase — each maps to any object or custom field on the other side.

How changes propagate between Snowflake and Supabase

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.

Snowflake Supabase Sub-second propagation

DetectionChanges in Snowflake are captured at the source via change data capture — no polling loop against its API. The setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism.

DeliveryEach detected change is applied to Supabase as a row-level write, with types converted between the two schemas.

Supabase Snowflake Sub-second propagation

DetectionSupabase pushes changes as they happen — webhook events backed by change data capture. Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime.

DeliveryEach detected change is applied to Snowflake as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Snowflake: No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time.
  • Supabase: SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits.
What ships with Snowflake ⇄ Supabase

Connect Snowflake and Supabase for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Snowflake–Supabase connection.

Real-time

Two-way sync

Changes in Snowflake or Supabase instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Snowflake or Supabase 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 Snowflake or Supabase record.

Observability

Monitoring

Track your Snowflake ⇄ Supabase sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Snowflake and Supabase.

How the Snowflake and Supabase connectors work

Snowflake

Integration surface
SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API
Authentication
Dedicated Snowflake service user + role with RSA key-pair authentication (Stacksync-provided public key), created via a setup script requiring SECURITY_ADMIN and ACCOUNTADMIN roles
Change detection
Not explicitly stated; the setup script grants "create stream" on synced schemas (Snowflake streams), but the docs do not name the change-capture mechanism
Capabilities
read · write · CDC
Rate limits
No conventional API rate limits; cost and throughput are governed by virtual warehouse size and running time
Snowflake setup guide

Supabase

Integration surface
Direct PostgreSQL wire protocol connection, plus an auto-generated REST API (PostgREST)
Authentication
Database credentials (connection string) for SQL access; API keys (anon / service role) for the REST layer
Change detection
Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime; database webhooks can also fire on row changes
Capabilities
read · write · CDC · webhooks
Rate limits
SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits
How it works

How to connect Snowflake to Supabase — 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 Snowflake and Supabase 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
    Snowflake connected
    Supabase connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Snowflake and Supabase 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 · Snowflake ⇄ Supabase
    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
    Snowflake Supabase
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Snowflake and Supabase 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
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:

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 581 integrations available for Snowflake and Supabase.

Popular · 8 of 581
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