{"id":18886,"date":"2025-12-22T18:02:35","date_gmt":"2025-12-22T23:02:35","guid":{"rendered":"https:\/\/www.iri.com\/blog\/?p=18886"},"modified":"2026-10-02T16:19:49","modified_gmt":"2026-10-02T20:19:49","slug":"connecting-databricks-delta-tables","status":"publish","type":"post","link":"https:\/\/www.iri.com\/blog\/iri\/iri-workbench\/connecting-databricks-delta-tables\/","title":{"rendered":"Connecting Databricks Delta Tables"},"content":{"rendered":"<p><em><strong>Abstract<\/strong>: This article covers the necessary JDBC and ODBC connectivity steps to reach Azure Databricks Delta tables from IRI Workbench and the CoSort SortCL engine used in structured data management operations in the Voracity platform ecosystem, especially IRI FieldShield data classification and masking jobs.<\/em><\/p>\n<p><a href=\"https:\/\/azure.microsoft.com\/en-us\/products\/databricks\"><span style=\"font-weight: 400;\">Azure Databricks<\/span><\/a><span style=\"font-weight: 400;\"> uses a \u201clakehouse\u201d architecture, which means it supports both structured and unstructured sources.<\/span><span style=\"font-weight: 400;\"> <span id='easy-footnote-1-18886' class='easy-footnote-margin-adjust'><\/span><span class='easy-footnote'><a href='https:\/\/www.iri.com\/blog\/iri\/iri-workbench\/connecting-databricks-delta-tables\/#easy-footnote-bottom-1-18886' title='&lt;i&gt;Because the &lt;\/i&gt;&lt;a href=&quot;https:\/\/www.iri.com\/produts\/fieldshield&quot;&gt;&lt;i&gt;IRI FieldShield&lt;\/i&gt;&lt;\/a&gt;&lt;i&gt; data masking tool only supports structured sources, the main focus of this article will be on Databricks Delta Tables.'><sup>1<\/sup><\/a><\/span><\/i><\/span><\/p>\n<p><span style=\"font-weight: 400;\">At the time of writing, Microsoft has made the creation of a new Databricks to support Unity Catalog by default. This forces a three-tiered system: Catalog, Schema, Table. <\/span><a href=\"https:\/\/www.iri.com\/products\/cosort\/sortcl\"><span style=\"font-weight: 400;\">SortCL<\/span><\/a><span style=\"font-weight: 400;\">-driven jobs (like FieldShield for data masking) in the <\/span><a href=\"https:\/\/www.iri.com\/products\/workbench\"><span style=\"font-weight: 400;\">IRI Workbench GUI<\/span><\/a><span style=\"font-weight: 400;\"> now support both Unity Catalog and legacy environments that don\u2019t use catalogs.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Delta tables support ETL processes that use SQL commands. And because Azure supplies both <\/span><a href=\"https:\/\/www.databricks.com\/spark\/jdbc-drivers-archive\"><span style=\"font-weight: 400;\">JDBC<\/span><\/a><span style=\"font-weight: 400;\"> and <\/span><a href=\"https:\/\/www.databricks.com\/spark\/odbc-drivers-download\"><span style=\"font-weight: 400;\">ODBC<\/span><\/a><span style=\"font-weight: 400;\"> drivers, once these connections are made in IRI Workbench, IRI Voracity data management platform tools can use the commands and drivers to manipulate data in the delta tables in data discovery, integration, migration, governance, and analytic <\/span><a href=\"https:\/\/www.iri.com\/products\/voracity\/technical-details#capabilities\"><span style=\"font-weight: 400;\">operations<\/span><\/a><span style=\"font-weight: 400;\">..\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Note that there is also a YouTube tutorial <\/span><a href=\"https:\/\/youtu.be\/-2R6WoAl3e8?si=MZbFJrwNKPsmk6U8\"><span style=\"font-weight: 400;\">here<\/span><\/a><span style=\"font-weight: 400;\"> for those who prefer visual, step-by-step instructions to the connection requirements documented below.<\/span><\/p>\n<h2><strong>JDBC Setup<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">The JDBC driver is required to enumerate and search tables from the IRI Workbench <\/span><a href=\"https:\/\/www.iri.com\/products\/workbench\/fieldshield-gui\"><span style=\"font-weight: 400;\">GUI for FieldShield<\/span><\/a><span style=\"font-weight: 400;\">, built on Eclipse. A future release of the <\/span><a href=\"https:\/\/www.iri.com\/products\/darkshield\"><span style=\"font-weight: 400;\">IRI DarkShield<\/span><\/a><span style=\"font-weight: 400;\"> data masking will also support Databricks delta tables through this driver.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Once the JDBC driver is downloaded from the links provided above, the next step is to get the following properties:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">JDBC URL<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">HTTP path<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Server Hostname<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">OAuth URL<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Access Token<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">These properties can be found in the Databricks portal under SQL Warehouses. Select the SQL Warehouse to use and go to the Connection details tab.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18892\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Connection-details-tab.png\" alt=\"Azure Databricks SQL Warehouse connection details showing server hostname, HTTP path, JDBC URL, and OAuth URL\" width=\"536\" height=\"561\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Connection-details-tab.png 710w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Connection-details-tab-287x300.png 287w\" sizes=\"(max-width: 536px) 100vw, 536px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">The image above shows the Databricks UI and where to find the JDBC properties to establish a connection. Note that the version of the JDBC driver downloaded dictates the JDBC URL format.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">On the same page, in the top right-hand corner, there is an option to create an access token. This token will act like a password for users to log in. This example uses an access token.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18893\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/access-token-1024x540.png\" alt=\"Azure Databricks developer settings for generating a personal access token\" width=\"666\" height=\"351\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/access-token-1024x540.png 1024w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/access-token-300x158.png 300w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/access-token-768x405.png 768w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/access-token.png 1030w\" sizes=\"(max-width: 666px) 100vw, 666px\" \/><\/p>\n<h2><strong>Inside IRI Workbench<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">Now that all the properties have been obtained and the driver has been downloaded, the focus will shift to Workbench to set up the JDBC connection.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the <\/span><i><span style=\"font-weight: 400;\">Data Source Explore<\/span><\/i><span style=\"font-weight: 400;\">r tab, select the new connection profile icon and select the Azure Databricks profile. (Image below for more context).<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18894\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/select-Azure-Databricks-1024x582.png\" alt=\"IRI Workbench New Connection Profile dialog with Azure Databricks selected\" width=\"779\" height=\"443\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/select-Azure-Databricks-1024x582.png 1024w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/select-Azure-Databricks-300x171.png 300w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/select-Azure-Databricks-768x437.png 768w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/select-Azure-Databricks.png 1041w\" sizes=\"(max-width: 779px) 100vw, 779px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Give the connection a name that provides the user with context about the environment or data Databricks is hosting. Once a name is given, select next, and you will see the following page.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18896\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/specify-a-driver-and-connection-details.png\" alt=\"IRI Workbench dialog for specifying an Azure Databricks JDBC driver and connection details\" width=\"439\" height=\"342\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/specify-a-driver-and-connection-details.png 503w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/specify-a-driver-and-connection-details-300x234.png 300w\" sizes=\"(max-width: 439px) 100vw, 439px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">On the page above, select the wheel icon in the top-right corner to create a new driver definition. A new pop-up window will appear, as shown in the image below.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18897\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/specify-a-driver-template-and-definition-name.png\" alt=\"IRI Workbench New Driver Definition dialog with the Azure Databricks JDBC Driver template selected\" width=\"455\" height=\"381\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/specify-a-driver-template-and-definition-name.png 579w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/specify-a-driver-template-and-definition-name-300x251.png 300w\" sizes=\"(max-width: 455px) 100vw, 455px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">This dialog is where key JDBC configuration settings, including the JDBC driver path, are set. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Select the only available driver template in the middle of the screen, then click the JAR List tab.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18898\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/JAR-List-tab.png\" alt=\"IRI Workbench JAR List tab for adding the Databricks JDBC driver file\" width=\"516\" height=\"433\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/JAR-List-tab.png 576w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/JAR-List-tab-300x252.png 300w\" sizes=\"(max-width: 516px) 100vw, 516px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Select the Jar and then select the <\/span><i><span style=\"font-weight: 400;\">Edit JAR\/ZIP\u2026 <\/span><\/i><span style=\"font-weight: 400;\">\u00a0to open the file browser and select the JDBC jar file needed for Azure Databricks. After selecting the correct jar file, it will appear here; e.g.:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18899\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/selecting-the-correct-jar-file.png\" alt=\"IRI Workbench showing the selected Databricks JDBC JAR file in the driver definition\" width=\"516\" height=\"433\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/selecting-the-correct-jar-file.png 579w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/selecting-the-correct-jar-file-300x252.png 300w\" sizes=\"(max-width: 516px) 100vw, 516px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Next, click on the <\/span><i><span style=\"font-weight: 400;\">Properties<\/span><\/i><span style=\"font-weight: 400;\"> tab and paste the JDBC URL:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18900\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Properties-tab_-JDBC-URL.png\" alt=\"IRI Workbench driver properties showing the Databricks JDBC connection URL\" width=\"521\" height=\"249\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Properties-tab_-JDBC-URL.png 557w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Properties-tab_-JDBC-URL-300x143.png 300w\" sizes=\"(max-width: 521px) 100vw, 521px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Click <\/span><i><span style=\"font-weight: 400;\">OK<\/span><\/i><span style=\"font-weight: 400;\"> at the bottom of the <\/span><i><span style=\"font-weight: 400;\">Provide Driver Details <\/span><\/i><span style=\"font-weight: 400;\">tab, and the pop-up window will return to the original setup page.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Specify all the properties in their respective text boxes. Leave the DB Name as default and click <\/span><i><span style=\"font-weight: 400;\">Test Connection<\/span><\/i><span style=\"font-weight: 400;\"> to verify that Workbench can connect to the Databricks source.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18902\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/databrick-connection-properties.png\" alt=\"IRI Workbench Azure Databricks connection properties with host, port, HTTP path, token, and JDBC URL\" width=\"506\" height=\"454\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/databrick-connection-properties.png 627w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/databrick-connection-properties-300x269.png 300w\" sizes=\"(max-width: 506px) 100vw, 506px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">If everything works, this pop-up window will appear:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18903\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/success-popup-window.png\" alt=\"IRI Workbench success message confirming the Azure Databricks JDBC connection\" width=\"485\" height=\"124\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/success-popup-window.png 512w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/success-popup-window-300x77.png 300w\" sizes=\"(max-width: 485px) 100vw, 485px\" \/><\/p>\n<h2><span style=\"font-weight: 400;\">\u00a0<\/span><strong>ODBC Setup<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">An ODBC connection is required by the back-end CoSort <\/span><a href=\"https:\/\/www.iri.com\/products\/cosort\/sortcl\"><span style=\"font-weight: 400;\">SortCL<\/span><\/a><span style=\"font-weight: 400;\"> engine powering FieldShield to read data from the delta tables, mask it externally, and write the masked data back to the user&#8217;s desired target (tables, files, or other RDB platforms).\u00a0<\/span><\/p>\n<h3>Configure the Simba Spark ODBC Driver<\/h3>\n<p><span style=\"font-weight: 400;\">To set up the ODBC connection, run the ODBC installer downloaded from the Databricks site. Once the installer is finished, open the Windows search bar and type <\/span><i><span style=\"font-weight: 400;\">ODBC Data Source Administrator (64-bit)<\/span><\/i><span style=\"font-weight: 400;\">.\u00a0\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The following application dialog will open:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18904 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/ocdc-data-source-admin.png\" alt=\"Windows ODBC Data Source Administrator showing the Simba Spark ODBC Driver\" width=\"582\" height=\"404\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/ocdc-data-source-admin.png 582w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/ocdc-data-source-admin-300x208.png 300w\" sizes=\"(max-width: 582px) 100vw, 582px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">On the right-hand side of the window, select the <\/span><i><span style=\"font-weight: 400;\">Add\u2026<\/span><\/i><span style=\"font-weight: 400;\"> button and look for the <\/span><i><span style=\"font-weight: 400;\">Simba Spark ODBC Driver<\/span><\/i><span style=\"font-weight: 400;\"> and select finish. This is the driver that will be used in order to create a connection to the Databricks source.<\/span><\/p>\n<p>A new pop-up window will appear to configure the ODBC connections with all the properties that were also used in the JDBC connection portion of this blog.<\/p>\n<p><span style=\"font-weight: 400;\">Apply a data source name to the connection and do the following:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Host(s) relate to the server hostname.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Port &#8211; default is 443<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Authentication set to OAuth 2.0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Thrift Transport set to HTTP<\/span><\/li>\n<\/ul>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18905 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-name.png\" alt=\"Simba Spark ODBC Driver setup for Azure Databricks with host, port, OAuth, and HTTP transport settings\" width=\"403\" height=\"769\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-name.png 403w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-name-157x300.png 157w\" sizes=\"(max-width: 403px) 100vw, 403px\" \/><\/p>\n<h3>Configure OAuth and HTTP Settings<\/h3>\n<p><span style=\"font-weight: 400;\">Select the <\/span><i><span style=\"font-weight: 400;\">OAuth Options\u2026<\/span><\/i><span style=\"font-weight: 400;\"> button to paste the access token. Click OK when done.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18906 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/OAuth-Options.png\" alt=\"Simba Spark ODBC OAuth options showing token passthrough authentication and an access token\" width=\"453\" height=\"124\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/OAuth-Options.png 453w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/OAuth-Options-300x82.png 300w\" sizes=\"(max-width: 453px) 100vw, 453px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">At the bottom of the page, select the <\/span><i><span style=\"font-weight: 400;\">Client Secret Encryption Options\u2026<\/span><\/i><span style=\"font-weight: 400;\"> This allows you to save the access token while encrypting it to keep it safe.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18907 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Client-Secret-Encryption-Options.png\" alt=\"Simba Spark OAuth settings with client secret encryption options for securing the Databricks access token\" width=\"457\" height=\"535\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Client-Secret-Encryption-Options.png 457w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Client-Secret-Encryption-Options-256x300.png 256w\" sizes=\"(max-width: 457px) 100vw, 457px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">There are two options: <\/span><i><span style=\"font-weight: 400;\">Current User Only <\/span><\/i><span style=\"font-weight: 400;\">(accessible\u00a0<\/span><span style=\"font-weight: 400;\"><span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\">only to the specific user) and\u00a0<em>All Users of this Machine<\/em> (accessible to<\/span>\u00a0everyone).<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18908\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Current-User-Only.png\" alt=\"Password Options dialog for encrypting Databricks credentials for the current user or all machine users\" width=\"316\" height=\"138\" \/><\/p>\n<p><span style=\"font-weight: 400;\">At the bottom, select the <\/span><i><span style=\"font-weight: 400;\">HTTP Options\u2026<\/span><\/i><span style=\"font-weight: 400;\"> to paste the HTTP path. Click OK when done.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18909\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/http-options.png\" alt=\"HTTP Properties dialog showing the Azure Databricks SQL Warehouse HTTP path\" width=\"478\" height=\"214\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/http-options.png 456w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/http-options-300x134.png 300w\" sizes=\"(max-width: 478px) 100vw, 478px\" \/><\/p>\n<h3>Set the Databricks Catalog and Test the Connection<\/h3>\n<p><span style=\"font-weight: 400;\">At the time of this writing, to support the Unity Catalog catalog option, a server-side property must be hard-coded to a specific catalog. This means that each catalog needs its own ODBC connection.<\/span><\/p>\n<p>To set this property, select Advanced options, Server Side Properties, and then Add \u2026<\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18910 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Advance-options_Server-Side-Properties.png\" alt=\"Simba Spark ODBC Driver setup with Advanced Options highlighted for Databricks configuration\" width=\"395\" height=\"775\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Advance-options_Server-Side-Properties.png 395w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/Advance-options_Server-Side-Properties-153x300.png 153w\" sizes=\"(max-width: 395px) 100vw, 395px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Here, the key is always\u00a0<em>databricks.catalog,<\/em> and the value is the name of the catalog you want to connect to.\u00a0Click OK until you are back to the main configuration page.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18912 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/databricks-catalog.png\" alt=\"Server-side property setting for the Databricks catalog in the Simba Spark ODBC connection\" width=\"442\" height=\"143\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/databricks-catalog.png 442w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/databricks-catalog-300x97.png 300w\" sizes=\"(max-width: 442px) 100vw, 442px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Finally, select the <\/span><i><span style=\"font-weight: 400;\">SSL Options<\/span><\/i><span style=\"font-weight: 400;\"> button and make sure that Enable SSL is selected.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Once all that is done, select the <\/span><i><span style=\"font-weight: 400;\">Test<\/span><\/i><span style=\"font-weight: 400;\"> button at the bottom of the <\/span><i><span style=\"font-weight: 400;\">Simba Spark ODBC Driver Setup <\/span><\/i><span style=\"font-weight: 400;\">page to ensure that the ODBC connection is set up correctly.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18913 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/test-results.png\" alt=\"ODBC Test Results confirming a successful connection to the Azure Databricks data source\" width=\"365\" height=\"330\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/test-results.png 365w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/test-results-300x271.png 300w\" sizes=\"(max-width: 365px) 100vw, 365px\" \/><\/p>\n<h2><strong>Inside IRI Workbench<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">Now that both JDBC and ODBC connections have been created, the next step is to ensure they are linked.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To do that, in Workbench, go to IRI Preferences and then select the twisty next to IRI to see more options.<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18914 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/IRI-preferences-window.png\" alt=\"IRI Workbench Preferences window showing Connection Registry settings\" width=\"270\" height=\"458\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/IRI-preferences-window.png 270w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/IRI-preferences-window-177x300.png 177w\" sizes=\"(max-width: 270px) 100vw, 270px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Select the twisty on <\/span><i><span style=\"font-weight: 400;\">Connection<\/span><\/i> <i><span style=\"font-weight: 400;\">Registry<\/span><\/i><span style=\"font-weight: 400;\"> and then select Database Connection. Verify the bit version is set to 64 and click Refresh to see all the ODBC connections available:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18915\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/connection-registry.png\" alt=\"IRI Workbench Database Connection Registry listing available ODBC data source names\" width=\"691\" height=\"418\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/connection-registry.png 757w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/connection-registry-300x182.png 300w\" sizes=\"(max-width: 691px) 100vw, 691px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Select the ODBC connection that was just created and then click Edit. This window opens:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18916\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/odbc-connection.png\" alt=\"IRI Workbench Database Connection Registry dialog mapping an ODBC DSN to an Azure Databricks JDBC profile\" width=\"450\" height=\"559\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/odbc-connection.png 504w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/odbc-connection-241x300.png 241w\" sizes=\"(max-width: 450px) 100vw, 450px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">At the top of the page, you will see the name of the ODBC connection.\u00a0<\/span>Moving further down, make sure 64-bit is selected, and that <em>Add user name and password<\/em> is selected.<\/p>\n<p><span style=\"font-weight: 400;\">Next to User, specify \u2018token\u2019 and identify the password as the access token. Select the encrypt button next to both properties so that the access token will not appear as clear text in any SortCL (FieldShield data masking) job scripts.<\/span><\/p>\n<p>Finally, at the bottom of the page, select the drop-down menu and choose the JDBC connection created earlier to map the two connections.<\/p>\n<p><span style=\"font-weight: 400;\">Click OK and make sure that the mapping is \u201cActive\u201d as shown below:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18917\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/JDBC-connection-window.png\" alt=\"IRI Workbench Connection Registry showing an active Databricks ODBC and JDBC connection mapping\" width=\"438\" height=\"319\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/JDBC-connection-window.png 492w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/JDBC-connection-window-300x218.png 300w\" sizes=\"(max-width: 438px) 100vw, 438px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">Now Databricks is set up and ready for use with FieldShield and the rest of the SortCL-driven applications in the IRI Voracity ecosystem:<\/span><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-18918 size-full\" src=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-explorer.png\" alt=\"IRI Workbench Data Source Explorer displaying Azure Databricks catalogs, schemas, tables, and query results\" width=\"892\" height=\"394\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-explorer.png 892w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-explorer-300x133.png 300w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2025\/12\/data-source-explorer-768x339.png 768w\" sizes=\"(max-width: 892px) 100vw, 892px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">If you are interested specifically in masking data in the delta tables, you can learn how to define data classes, search methods, and RDB masking jobs in this FieldShield how-to summary article: <\/span><a href=\"https:\/\/www.iri.com\/blog\/data-protection\/how-to-mask-pii-in-a-database\/\"><span style=\"font-weight: 400;\">https:\/\/www.iri.com\/blog\/data-protection\/how-to-mask-pii-in-a-database\/<\/span><\/a><\/p>\n<p><span style=\"font-weight: 400;\">If you have any questions or need support,\u00a0<\/span><span style=\"font-weight: 400;\"><span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\">don&#8217;t hesitate to get in touch with\u00a0<a target=\"_blank\" rel=\"noopener\">support@iri.com<\/a><\/span>.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Abstract: This article covers the necessary JDBC and ODBC connectivity steps to reach Azure Databricks Delta tables from IRI Workbench and the CoSort SortCL engine used in structured data management operations in the Voracity platform ecosystem, especially IRI FieldShield data classification and masking jobs. Azure Databricks uses a \u201clakehouse\u201d architecture, which means it supports both<\/p>\n<div><a class=\"btn-filled btn\" href=\"https:\/\/www.iri.com\/blog\/iri\/iri-workbench\/connecting-databricks-delta-tables\/\" title=\"Connecting Databricks Delta Tables\">Read More<\/a><\/div>\n","protected":false},"author":160,"featured_media":18921,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[108,8,91,29,3],"tags":[201,2368,2326,2321,340,107,2370,14,15,1398,2371,2367,2329,2322,2330,2324,2369,2325,2335,2334,1388,520,789,850,2327,2332,2328,1815,2331,2333,2323],"class_list":["post-18886","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data-2","category-data-protection","category-iri-workbench","category-test-data","category-vldb-operations","tag-automate-database-test-data-generation","tag-azure-data-masking","tag-azure-data-platform","tag-azure-databricks","tag-data-governance","tag-data-integration","tag-data-lake-security","tag-data-masking","tag-data-security","tag-database-masking","tag-databricks-data-classification","tag-databricks-data-masking","tag-databricks-jdbc","tag-databricks-lakehouse","tag-databricks-odbc","tag-delta-lake","tag-delta-lake-protection","tag-delta-tables","tag-eclipse-based-tools","tag-etl-pipelines","tag-iri-darkshield","tag-iri-fieldshield","tag-iri-voracity","tag-iri-workbench","tag-jdbc-configuration","tag-oauth-authentication","tag-odbc-configuration","tag-pii-protection","tag-simba-spark-odbc-driver","tag-sql-warehouses","tag-unity-catalog"],"acf":[],"yoast_head":"<!-- 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