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Snowflake is a leading cloud data warehouse and a popular backbone for enterprise BI, analytics, data management, and governance initiatives. Snowflake offers features such as data sharing, real-time data processing, and secure data storage which makes it a common choice for cloud data consolidation.
The CData SSIS Components enhance SQL Server Integration Services by enabling users to easily import and export data from various sources and destinations.
In this article, we explore the data type mapping considerations when exporting to Snowflake and walk through how to migrate Google Cloud Storage data to Snowflake using the CData SSIS Components for Google Cloud Storage and Snowflake.
| Snowflake Schema | CData Schema |
|---|---|
|
NUMBER, DECIMAL, NUMERIC, INT, INTEGER, BIGINT, SMALLINT, TINYINT, BYTEINT |
decimal |
|
DOUBLE, FLOAT, FLOAT4, FLOAT8, DOUBLEPRECISION, REAL |
real |
|
VARCHAR, CHAR, STRING, TEXT, VARIANT, OBJECT, ARRAY, GEOGRAPHY |
varchar |
|
BINARY, VARBINARY |
binary |
|
BOOLEAN |
bool |
|
DATE |
date |
|
DATETIME, TIMESTAMP, TIMESTAMP_LTZ, TIMESTAMP_NTZ, TIMESTAMP_TZ |
datetime |
|
TIME |
time |
Timestamps: Snowflake supports three timestamp types:
By default the CData SSIS Components write timestamps to Snowflake as TIMESTAMP_NTZ unless manually configured.
Follow the steps below to specify properties required to connect to Google Cloud Storage.
You can connect without setting any connection properties for your user credentials. After setting InitiateOAuth to GETANDREFRESH, you are ready to connect.
When you connect, the Google Cloud Storage OAuth endpoint opens in your default browser. Log in and grant permissions, then the OAuth process completes
Service accounts have silent authentication, without user authentication in the browser. You can also use a service account to delegate enterprise-wide access scopes.
You need to create an OAuth application in this flow. See the Help documentation for more information. After setting the following connection properties, you are ready to connect:
The OAuth flow for a service account then completes.
๐ Configure the source connection (Salesforce is shown)With the Google Cloud Storage Source configured, we can configure the Snowflake connection and map the columns.
You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.
Download a free trial of the Google Cloud Storage SSIS Component to get started:
Download NowLearn more:
๐ Google Cloud Storage IconPowerful SSIS Source & Destination Components that allows you to easily connect SQL Server with Google Cloud Storage through SSIS Workflows.
Use the Google Cloud Storage Data Flow Components to synchronize with Google Cloud Storage Buckets, Objects, and more. Perfect for data synchronization, local back-ups, workflow automation, and more!