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Database ⇄ Data warehouse

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

Keep SingleStore 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.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect SingleStore and Snowflake

Connect SingleStore 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 SingleStore'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 SingleStore where the services that read from it get them at normal query latency.

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

Common use cases

  • Feed finance reconciliation models from ERP data landed in Snowflake on a continuous basis
  • Land CRM and ERP records in Snowflake continuously so BI reflects business systems without nightly batch ETL
  • Feed synced operational data into applications that need low-latency responses over fresh data.
  • Mirror CRM and SaaS objects into SingleStore tables to serve low-latency operational dashboards.

Operational data in the warehouse, minus the pipeline

Rows from SingleStore land in Snowflake as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Snowflake sync into SingleStore, 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.

What you can sync between SingleStore and Snowflake

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.

SingleStore objects Snowflake objects
Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys. Tables The main landing and activation target for synced records.
Databases The connection target containing the tables a sync addresses. Views Modeled projections used as the source side of outbound syncs.
Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans. Materialized Views Precomputed results synced outward for low-latency reads.
Views Read-only projections used as curated sync sources. Streams Row-level change records on a table, consumed to process deltas instead of full scans.
Reference Tables Small tables replicated to every node, often used for dimension data in syncs. Stages File staging areas used for bulk loads into synced tables.
Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs. Tasks Scheduled SQL used to transform synced data after it lands.
What ships with SingleStore ⇄ Snowflake

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

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

Trading partners

EDI

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

How the SingleStore and Snowflake connectors work

SingleStore

Integration surface
SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
Authentication
Database credentials
Change detection
Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by workspace or cluster size

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
How it works

How to connect SingleStore to Snowflake — 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 SingleStore 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    SingleStore connected
    Snowflake connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the SingleStore 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · SingleStore ⇄ Snowflake
    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
    SingleStore Snowflake
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

SingleStore and Snowflake integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for SingleStore and Snowflake.

Popular · 8 of 386
All SingleStore integrations All Snowflake integrations Browse all integrations
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