Migrating data from Databricks to Snowflake using CData SSIS Components.



Easily push Databricks data to Snowflake using the CData SSIS Tasks for Databricks and Snowflake.

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 Databricks data to Snowflake using the CData SSIS Components for Databricks and Snowflake.

Data Type Mapping

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

Special Considerations

  • Casing: Snowflake enforces an exact case match by default for identifiers, so it is common to run into issues that can be attributed to mismatched casing. Set the IgnoreCase property to True in your CData SSIS Components for Snowflake connection to resolve these issues. This property directly maps to the QUOTED_IDENTIFIERS_IGNORE_CASE property in Snowflake and specifies whether Snowflake will treat identifiers as case-sensitive.
  • Timestamps: Snowflake supports three timestamp types:

    • TIMESTAMP_NTZ: This timestamp stores UTC time with a specified precision. However, all operations are performed in the current session's time zone, controlled by the TIMEZONE session parameter.
    • TIMESTAMP_LTZ: This timestamp stores "wallclock" time with a specified precision. All operations are performed without taking any time zone into account.
    • TIMESTAMP_TZ: This timestamp stores UTC time together with an associated time zone offset. When a time zone isn't provided, the session time zone offset is used.

    By default the CData SSIS Components write timestamps to Snowflake as TIMESTAMP_NTZ unless manually configured.

About Databricks Data Integration

Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:

  • Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
  • Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
  • Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
  • Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.

While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.

Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.


Getting Started


Prerequisites

Create the project and add components

  1. Open Visual Studio and create a new Integration Services Project.
  2. Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
  3. Add a CData Databricks Source control and a CData Snowflake Destination control to the data flow task.

Configure the Databricks source

Follow the steps below to specify properties required to connect to Databricks.

  1. Double-click the CData Databricks Source to open the source component editor and add a new connection.
  2. In the CData Databricks Connection Manager, configure the connection properties, then test and save the connection.

    To connect to a Databricks cluster, set the properties as described below.

    Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.

    • Server: Set to the Server Hostname of your Databricks cluster.
    • HTTPPath: Set to the HTTP Path of your Databricks cluster.
    • Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
  3. After saving the connection, select "Table or view" and select the table or view to export into Snowflake, then close the CData Databricks Source Editor.

Configure the Snowflake destination

With the Databricks Source configured, we can configure the Snowflake connection and map the columns.

  1. Double-click the CData Snowflake Destination to open the destination component editor and add a new connection.
  2. In the CData Snowflake Connection Manager, configure the connection properties, then test and save the connection.
    • The component supports Snowflake user authentication, federated authentication, and SSL client authentication. To authenticate, set User and Password, and select the authentication method in the AuthScheme property. Starting with accounts created using Snowflake’s bundle 2024_08 (October 2024), password-based authentication is no longer supported due to security concerns. Instead, use alternative authentication methods such as OAuth or Private Key authentication.

    Other helpful connection properties

    • QueryPassthrough: When this is set to True, queries are passed through directly to Snowflake.
    • ConvertDateTimetoGMT: When this is set to True, the components will convert date-time values to GMT, instead of the local time of the machine.
    • IgnoreCase: A session parameter that specifies whether Snowflake will treat identifiers as case sensitive. Default: false(case is sensitive).
    • BindingType: There are two kinds of binding types: DEFAULT and TEXT. DEFAULT uses the binding type DATE for the Date type, TIME for the Time type, and TIMESTAMP_* for the Timestamp_* type. TEST uses the binding type TEXT for Date, Time, and Timestamp_* types.
  3. After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert.
  4. On the Column Mappings tab, configure the mappings from the input columns to the destination columns.

Run the project

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.

Ready to get started?

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Learn more:

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