Source connector

Snowflake connector

Snowflake integration for databases, warehouses and BI tools

Cloud data platform with separated storage and compute. Datrise captures Snowflake entities such as databases, schemas, tables, views, query history and warehouses, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Snowflake SQL API v2 + JDBC/ODBC drivers authenticates with OAuth 2.0, JWT, service account, incremental runs key on Snowflake Streams (METADATA$ACTION / METADATA$ISUPDATE) or a monotonic timestamp/sequence column, and Snowflake caps calls at No fixed requests-per-second API limit is published; MAX_CONCURRENCY_LEVEL defaults to 8 concurrent queries per warehouse cluster (a tunable, soft limit — extra queries queue rather than fail).

Of the 6 objects, 5 sync as upserts keyed on the primary key and 1 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `snowflake_databases`) with a schema derived from the Snowflake API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Snowflake pipeline page, and join the waitlist to get the Snowflake connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Snowflake data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
databases	snowflake_databases	Upsert by primary key, incremental on updated-at
schemas	snowflake_schemas	Upsert by primary key, incremental on updated-at
tables	snowflake_tables	Upsert by primary key, incremental on updated-at
views	snowflake_views	Upsert by primary key, incremental on updated-at
query history	snowflake_query_history	Append-only, incremental by timestamp
warehouses	snowflake_warehouses	Upsert by primary key, incremental on updated-at

Snowflake API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Snowflake SQL API v2 + JDBC/ODBC drivers
Authentication	OAuth 2.0, JWT, service account — The SQL API and drivers authenticate via key-pair JWT, OAuth bearer tokens, or Workload Identity Federation tokens for AWS/Azure/GCP service accounts.
Pagination	keyset — Ordinary SQL extraction pages via a keyset WHERE-clause watermark on a monotonic column; the SQL API v2 additionally retrieves numbered result partitions rather than a REST cursor.
Rate limit	No fixed requests-per-second API limit is published; MAX_CONCURRENCY_LEVEL defaults to 8 concurrent queries per warehouse cluster (a tunable, soft limit — extra queries queue rather than fail)
Incremental cursor	Snowflake Streams (METADATA$ACTION / METADATA$ISUPDATE) or a monotonic timestamp/sequence column — A Stream's offset lives inside the source table's Time Travel history and goes stale once it falls outside DATA_RETENTION_TIME_IN_DAYS, forcing a full re-select.
Webhooks	No
Bulk export	Yes — COPY INTO <location> bulk unload to a stage
Deletes detectable	Yes — A Streams row shows METADATA$ACTION = 'DELETE' for removed rows, and for the delete half of an update pair

Official API reference

What bites when replicating Snowflake

Table DATA_RETENTION_TIME_IN_DAYS defaults to just 1 day on Standard Edition (0-90 on Enterprise+); Streams reading a Standard-Edition table have a short window before losing their offset.
Snowflake auto-extends retention up to 14 days to protect an unconsumed Stream, but once a Stream is marked stale its offset is unusable and the pipeline must reinitialize with a full re-select.
MAX_CONCURRENCY_LEVEL defaults to 8 per warehouse but is a soft cap; Snowflake's own docs warn it may queue queries at 6, 4, or fewer under load, so set STATEMENT_QUEUED_TIMEOUT_IN_SECONDS to fail fast instead of hanging.
Snowpipe publishes no fixed latency SLA and Snowflake's own guidance recommends staging new files no more than once every 60 seconds for cost efficiency, so near-real-time delivery should not be assumed to be sub-minute.

Compare this against every other documented API

Popular destinations for Snowflake

Choose a destination below to open the ready pipeline page.

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Airtable
Relational spreadsheet destination for ops and go-to-market teams.
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Amazon Athena
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Amazon DynamoDB
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Amazon QuickSight
AWS serverless BI with SPICE and embedded analytics.
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Amazon Redshift
AWS petabyte-scale warehouse with Spectrum.
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Amazon S3 Data Lake
Object storage landing zone for parquet and snapshots.
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Apache Superset
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Azure Data Lake Storage
ADLS Gen2 object storage for analytics workloads.
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Azure Synapse
Microsoft analytics workspace with SQL pools.
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Snowflake connector FAQ

What Snowflake data does the connector extract?: 6 objects: databases, schemas, tables, views, query history and warehouses. Each lands in its own table with types preserved; history-style objects (1: query history) load as append-only streams.
Is the Snowflake integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Snowflake data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Snowflake → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Snowflake pipeline with guided onboarding

Join the waitlist to get priority access for Snowflake integrations with guided setup, schema-aware mapping, and production-grade incremental sync.