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This connector materializes Flow collections into tables in a Snowflake database. It allows both standard and delta updates.

The connector first uploads data changes to a Snowflake table stage. From there, it transactionally applies the changes to the Snowflake table. provides the latest connector image. You can also follow the link in your browser to see past image versions.


To use this connector, you'll need:

  • A Snowflake account that includes:
    • A target database, to which you'll materialize data
    • A schema — a logical grouping of database objects — within the target database
    • A virtual warehouse
    • A user with a role assigned that grants the appropriate access levels to these resources. See the script below for details.
  • Know your Snowflake account's host URL. This is formatted using your Snowflake account identifier, for example,
  • At least one Flow collection

If you haven't yet captured your data from its external source, start at the beginning of the guide to create a dataflow. You'll be referred back to this connector-specific documentation at the appropriate steps.


To meet the prerequisites, copy and paste the following script into the Snowflake SQL editor, replacing the variable names in the first six lines.

If you'd like to use an existing database, warehouse, and/or schema, be sure to set database_name, warehouse_name, and estuary_schema accordingly. If you specify a new name, the script will create the item for you. You can set estuary_role, estuary_user, and estuary_password to whatever you'd like.

Check the All Queries check box, and click Run.

set database_name = 'ESTUARY_DB';
set warehouse_name = 'ESTUARY_WH';
set estuary_role = 'ESTUARY_ROLE';
set estuary_user = 'ESTUARY_USER';
set estuary_password = 'secret';
set estuary_schema = 'ESTUARY_SCHEMA';
-- create role and schema for Estuary
create role if not exists identifier($estuary_role);
grant role identifier($estuary_role) to role SYSADMIN;
-- Create snowflake DB
create database if not exists identifier($database_name);
use database identifier($database_name);
create schema if not exists identifier($estuary_schema);
-- create a user for Estuary
create user if not exists identifier($estuary_user)
password = $estuary_password
default_role = $estuary_role
default_warehouse = $warehouse_name;
grant role identifier($estuary_role) to user identifier($estuary_user);
grant all on schema identifier($estuary_schema) to identifier($estuary_role);
-- create a warehouse for estuary
create warehouse if not exists identifier($warehouse_name)
warehouse_size = xsmall
warehouse_type = standard
auto_suspend = 60
auto_resume = true
initially_suspended = true;
-- grant Estuary role access to warehouse
grant USAGE
on warehouse identifier($warehouse_name)
to role identifier($estuary_role);
-- grant Estuary access to database
grant CREATE SCHEMA, MONITOR, USAGE on database identifier($database_name) to role identifier($estuary_role);
-- change role to ACCOUNTADMIN for STORAGE INTEGRATION support to Estuary (only needed for Snowflake on GCP)
grant CREATE INTEGRATION on account to role identifier($estuary_role);
use role sysadmin;


To use this connector, begin with data in one or more Flow collections. Use the below properties to configure a Snowflake materialization, which will direct one or more of your Flow collections to new Snowflake tables.



/accountAccountThe Snowflake account identifierstringRequired
/databaseDatabaseName of the Snowflake database to which to materializestringRequired
/hostHost URLThe Snowflake Host used for the connection. Example: (do not include the protocol).stringRequired
/passwordPasswordSnowflake user passwordstringRequired
/roleRoleRole assigned to the userstring
/schemaSchemaDatabase schema for bound collection tables (unless overridden within the binding resource configuration) as well as associated materialization metadata tablesstringRequired
/userUserSnowflake usernamestringRequired
/warehouseWarehouseName of the data warehouse that contains the databasestring
/advancedAdvanced OptionsOptions for advanced users. You should not typically need to modify these.object
/advanced/updateDelayUpdate DelayPotentially reduce active warehouse time by increasing the delay between updates.string


/tableTableTable namestringRequired
/schemaAlternative SchemaAlternative schema for this tablestring
/delta_updatesDelta updatesWhether to use standard or delta updatesboolean


account: acmeCo
database: acmeCo_db
password: secret
schema: acmeCo_flow_schema
user: snowflake_user
warehouse: acmeCo_warehouse
# If you have multiple collections you need to materialize, add a binding for each one
# to ensure complete data flow-through
- resource:
table: ${table_name}
source: ${PREFIX}/${source_collection}

Delta updates

This connector supports both standard (merge) and delta updates. The default is to use standard updates.

Enabling delta updates will prevent Flow from querying for documents in your Snowflake table, which can reduce latency and costs for large datasets. If you're certain that all events will have unique keys, enabling delta updates is a simple way to improve performance with no effect on the output. However, enabling delta updates is not suitable for all workflows, as the resulting table in Snowflake won't be fully reduced.

You can enable delta updates on a per-binding basis:

- resource:
table: ${table_name}
delta_updates: true
source: ${PREFIX}/${source_collection}

Performance considerations

Optimizing performance for standard updates

When using standard updates for a large dataset, the collection key you choose can have a significant impact on materialization performance and efficiency.

Snowflake uses micro partitions to physically arrange data within tables. Each micro partition includes metadata, such as the minimum and maximum values for each column. If you choose a collection key that takes advantage of this metadata to help Snowflake prune irrelevant micro partitions, you'll see dramatically better performance.

For example, if you materialize a collection with a key of /user_id, it will tend to perform far worse than a materialization of /date, /user_id. This is because most materializations tend to be roughly chronological over time, and that means that data is written to Snowflake in roughly /date order.

This means that updates of keys /date, /user_id will need to physically read far fewer rows as compared to a key like /user_id, because those rows will tend to live in the same micro-partitions, and Snowflake is able to cheaply prune micro-partitions that aren't relevant to the transaction.

Reducing active warehouse time

Snowflake compute is priced per second of activity, with a minimum of 60 seconds. Inactive warehouses don't incur charges. To keep costs down, you'll want to minimize your warehouse's active time.

Like other Estuary connectors, this is a real-time connector that materializes documents using continuous transactions. Every time a Flow materialization commits a transaction, your warehouse becomes active.

If your source data collection or collections don't change much, this shouldn't cause an issue; Flow only commits transactions when data has changed. However, if your source data is frequently updated, your materialization may have frequent transactions that result in excessive active time in the warehouse, and thus a higher bill from Snowflake.

To mitigate this, we recommend a two-pronged approach:

  • Configure your Snowflake warehouse to auto-suspend after 60 seconds.

    This ensures that after each transaction completes, you'll only be charged for one minute of compute, Snowflake's smallest granularity.

    Use a query like the one shown below, being sure to substitute your warehouse name:

    ALTER WAREHOUSE ESTUARY_WH SET auto_suspend = 60;
  • Configure the materialization's update delay by setting a value in the advanced configuration.

For example, if you set the warehouse to auto-suspend after 60 seconds and set the materialization's update delay to 30 minutes, you can incur as little as 48 minutes per day of active time in the warehouse.

Reserved words

Snowflake has a list of reserved words that must be quoted in order to be used as an identifier. Flow automatically quotes fields that are in the reserved words list. You can find this list in Snowflake's documentation here and in the table below.


In Snowflake, objects created with quoted identifiers must always be referenced exactly as created, including the quotes. Otherwise, SQL statements and queries can result in errors. See the Snowflake docs.

Reserved words