![]() |
VOOZH | about |
This article illustrates using the Databricks ADO.NET Data Provider within a SQL Server SSIS workflow for the direct transfer of Databricks data to a Microsoft SQL Server database. It's worth noting that the identical process detailed below is applicable to any CData ADO.NET Data Providers, enabling the direct connection of SQL Server with remote data through SSIS.
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
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.
In the Data Flow screen, add an ADO.NET Source and an OLE DB Destination from the toolbox.
๐ The components used in the data task in this example.In the connection manager, enter the connection details for Databricks data.
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.
Open the DataReader editor and set the following information:
SELECT City, CompanyName FROM Customers WHERE Country = 'US'
Open the OLE DB Destination and enter the following information in the Destination Component Editor.
Configure any properties you wish on the Mappings screen.
๐ Input and destination columns in the OLE DB Destination Editor.Download a free trial of the Databricks Data Provider to get started:
Download NowLearn more:
๐ Databricks IconRapidly create and deploy powerful .NET applications that integrate with Databricks.