Snowflake Beta

The Fivetran Snowflake connector allows you to sync tables and views from one Snowflake database to your destination. We can sync any number of schemas, tables, and views from within your Snowflake database. Fivetran supports both regular and materialized views.

TIP: If you want to sync multiple Snowflake databases, we recommend that you create a connector for each database.

Features

Feature Name	Supported	Notes
		All tables and fields
		All tables and fields
		Column level, table level, and schema level

		Table level


Priority-first sync
Fivetran data models
		, , and

Setup guide

Follow our to connect your Snowflake database with Fivetran.

Sync overview

Once Fivetran is connected to your database, we pull a full dump of all selected data from your database. We then use Fivetran Teleport Sync to pull all your new and changed data at regular intervals. If data in your source database changes (for example, you add new tables or change a data type), Fivetran automatically detects and persists these changes into your destination.

Schema information

Fivetran tries to replicate the exact schema, tables and views from your Snowflake source database to your destination.

We name the source schema with the dataset name you provided in the connector setup form. We replicate the source's tables and views to the destination schema. We name the destination schema with the connector name appended by the dataset name. For example, if the connector name is snowflake_db and the dataset name is fivetran_schema, the destination schema name is snowflake_db_fivetran_schema.

Type transformations and mapping

As we extract your data, we match Snowflake data types to types that Fivetran supports. If we don't support a data type, we automatically change that type to the closest supported type or, in some cases, don't load that data at all. Our system automatically skips columns with data types that we don't accept or transform.

The following table illustrates how we transform your Snowflake data types into Fivetran-supported types for regular and primary key columns:

Data Type	Fivetran Type	Regular Column Support	Primary Key Support (Teleport)
NUMBER* (s = 0)	One of the following types: - SHORT (p <= 4) - INTEGER (p <= 9) - LONG (p <= 18)	Yes	Yes
NUMBER* (s > 0 OR p > 18)	BIGDECIMAL	Yes	No
FLOAT	BIGDECIMAL	Yes	No
TEXT (with ASCII only)	STRING	Yes	Yes (Up to a length of 256 bytes)
TEXT (with Unicode)	STRING	Yes	No
TEXT	STRING	Yes	Yes (Up to a length of 256 bytes)
BOOLEAN	BOOLEAN	Yes	No
TIME	STRING	Yes	No
TIMESTAMP_NTZ	LOCALDATETIME	Yes	No
TIMESTAMP_TZ	INSTANT	Yes	No
TIMESTAMP_LTZ	INSTANT	Yes	No
DATE	LOCALDATE	Yes	No
BINARY	BINARY	Yes	Yes (Length must be a multiple of 4 up to a max of 128 bytes and values must not contain leading zeros)
VARIANT	STRING	Yes	No
ARRAY	STRING	Yes	No
OBJECT	JSON	Yes	No
GEOGRAPHY	JSON	Yes	No
GEOMETRY	JSON	Yes	No

*NOTE: The NUMBER type has a precision p and a scale s. The maximum supported values are p = 38 and s = 37. If we detect a precision or scale that exceeds those maximums, we map that data to the STRING data type and update the destination column type to STRING.

Updating data

Fivetran performs incremental updates of any new or modified data from your source database. We use Fivetran Teleport Sync, our proprietary database replication method, to fetch only the data that has changed since our last sync. Learn more in our .

Fivetran Teleport Sync's queries perform the following operations on your database:

Do a full table scan of each synced table
Perform calculations on all values in each synced table's rows
Aggregate a compressed table snapshot in the database's memory

For optimum Fivetran Teleport Sync performance, we recommend that you make the following resources available in your database:

1 GB Free RAM
1 Free CPU Core
IOPS (Teleport Sync times decrease linearly with an increase of available IOPS).

NOTE: Teleport captures deletes differently than log-based replication mechanisms. Learn more in our .

Automatic table re-syncs

For tables with a primary key, we support ADD COLUMN DDL operations with null or default static values. All other table or column alterations trigger an automatic table re-sync. For tables without a primary key, any DDL operation triggers an automatic table re-sync.

Tables with a primary key

We merge changes to tables with primary keys into the corresponding tables in your destination:

An INSERT in the source table generates a new row in the destination with _fivetran_deleted = FALSE.
A DELETE in the source table updates the corresponding row in the destination with _fivetran_deleted = TRUE.
An UPDATE in the source table updates the data in the corresponding row in the destination.

If any primary key column has an unsupported data type, then the table is automatically treated as primary key-less (which means create table permissions are required on the database or the workspace database).

Tables without a primary key

For tables without a primary key, we designate the _fivetran_id column as the primary key. We populate this column with the hash of the values of each row.

Recommendations

If you want to sync tables with primary keys, we recommend that the combined size of all the tables does not exceed 100 GB.
If you want to sync tables without primary keys, we recommend that the combined size of all the tables does not exceed 10 GB. Contact for assistance with your syncs.