Organizations use Tableau to create Data Visualizations like charts and graphs and share them with their teams or friends. Tableau enables users to access data from Data Warehouses and Databases to create reports and dashboards. While accessing data from Databases, Tableau uses JDBC drivers that provide a standard way of connecting to the Databases. This article will take you through a Tableau JDBC connection.
Tableau consists of some built-in connectors to access data from different sources. However, Tableau also supports custom connectors called Other Databases (JDBC) connectors to integrate various Data Sources. In this tutorial, you will learn to connect Tableau with your Database using JDBC drivers and Other Databases (JDBC) connectors. But before getting started with the Tableau JDBC connection, let’s discuss this robust BI platform in brief.
Prerequisites
For a clear understanding of the Tableau JDBC connection, you must be conscious of the need for this integration and the benefits that a Tableau JDBC connection serves.
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What is Tableau?
Developed in 2003, Tableau is a popular Data Visualization tool that can process any data into meaningful insights. It provides simple drag-and-drop actions through which users can create graphs, dashboards, different charts, and maps to understand their data. With Tableau, even non-technical professionals and users can convert their data into interactive, understandable graphics using widgets and templates.
Tableau has the capability of creating visual information that communicates more effectively rather than Spreadsheets or Text formats. Business Intelligence (BI) professionals can use Tableau to create and publish their dashboards to several teams in organizations. Tableau users can further interact and engage with data graphically to quickly uncover business insights. As a result, Tableau can reduce the burden on the IT Teams or the Technical Teams of gaining data insights.
Now that you have a basic understanding of what Tableau is, let’s dive straight into the Tableau JDBC connection.
Key Features of Tableau
Here a some of the key features responsible for the immense popularity of Tableau.
- Multipurpose Dashboard: Tableau comes with an intuitive dashboard that allows even non-technical users to perform quick Data Analysis and create visualizations. Users can create high-level graphs and dashboards using its easy-to-use drag and drop functionality.
- Extensive Data Sources: Tableau houses over 200 connectors and drivers that allow users to securely connect to multiple third-party applications and external data sources such as Relational Databases, Big Data, Cloud, Spreadsheets, and more.
- Powerful Collaboration: Users working on different projects can collaborate with each other on Tableau. Users can further share the dashboard on the Cloud, making it accessible to anyone from anywhere.
- Advanced Visualizations: Tableau has a vast collection of advanced Data Visualization techniques. Users can easily visualize data in the form of Charts, Tables, Graphs, Plots, Maps, etc.
- Tableau Community: Tableau has a large community of active users, Developers, and Analysts. Being a part of this community allows you to continuously learn, upskill, build powerful connections, and offer mentorship to newcomers.
Tableau JDBC Integration
You can follow the below-mentioned methods to establish a Tableau JDBC integration.
Tableau Other Databases (JDBC) Connectors Integration
Tableau supports official connectors like Athena, Amazon Redshift, JSON Files, Google Analytics, Google Ads, and more to integrate Data Sources. However, it may happen that the Data Source or the Data Type you are looking for is not in the list, then you can connect your Data Source using JDBC drivers with Other Databases (JDBC) connectors.
JDBC drivers require Java, which makes it platform-independent. All the Tableau applications from version 2020.2 are wrapped with Java Runtime. Consequently, you do not have to install them separately. Let’s get started.
Prerequisites
When you start Tableau Desktop of version 2021.4, under the “Connect” tab, you will see the file and data types supported by it. Select “More” to see the complete list. Tableau provides built-in connectors that are built and optimized for different Data Sources.
- Specify the Right JDBC Driver
JDBC drivers consist of .jar files, which need to be placed in the Tableau folder as follows.
Windows: C:Program FilesTableauDrivers
Mac: ~/Library/Tableau/Drivers
Linux: /opt/tableau/tableau_driver/jdbc
You must have the below requirements:
- Read permissions on the
.jar files.
- Tableau with JDBC 4.0 or later driver.
- Tableau Type 4 JDBC driver.
- 64-bit version of Java 8.
Dialects are used as a configuration setting for platform-independent software that allows other software to translate generic SQL statements into specific DDL or DML. Other Databases (JDBC) connectors use the below dialects that establish how Tableau translates the SQL queries sent to the database.
- MySQL
- PostgreSQL
- Generic SQL-92
- Gather the Connection Information
When you connect with the JDBC driver, you must enter the JDBC URL in the URL field. For example, look at the JDBC URL below.
jdbc:postgresql://www.exampledatabase.com:5432/databasename
- jdbc: It is used as the ‘jdbc’ prefix.
- postgresql: It is used to define the class of the JDBC driver you are using. These drivers have subprotocols assigned with them, such as ‘postgresql’ for PostgreSQL or ‘mysql’ for MySQL.
- www.exampledatabase.com: It is used as the network address to your Database Server. It can be a hostname or an IP address.
- 5432: It is the port number where the Database is responding to the network address.
- databasename: It is the name of your Database or Schema on your Database Server.
Now, you can select the dialect of your database you want to use, like MySQL, PostgreSQL, or SQL-92. Keep in handy the username and password for signing in to the Tableau Server.
You can follow Customizing JDBC Connections using Properties File for more details.
Make the Tableau JDBC Connection
Follow the below steps to connect your data using the JDBC driver.
- Start Tableau. Under the “Connect” tab, select Other Databases (JDBC). Click on “More” under the “To a Server” tab for the complete list of data connections.
- Enter the JDBC connection string in the URL field.
- Select the dialect from the drop-down list.
- Enter the username and password for signing in to the server.
- (Optional) Browse to the JDBC properties file to customize the behavior of connectors.
- Finally, click on Sign in.
Configuration for Cross-platform Portability
When you work with an inbuilt JDBC connection, it is essential to add additional configuration to ensure that the Workbooks and Data Sources you create can be used on different computers and platforms.
The driver must be installed to match the Workbook or Data Source connection for cross-platform portability. With Tableau, you can create the Other Databases (JDBC) connectors Data Source that connects using the associated JDBC driver installed on your computer.
This Data Source can perform the following actions:
- You can publish your Data Source to Tableau Server, but for that purpose, you need to tell The Tableau Server Administrator to install the associated JDBC driver. It will make the Data Source accessible to others.
- You can also Email the Data Source to your team or coworkers. They need to install the associated JDBC driver on their computers to open the Data Source in Tableau Desktop.
If you try to open a Workbook or Data Source created using Other Databases (JDBC) connectors, you will get an error if you do not install the associated JDBC driver. The error will include a message like “no suitable driver“. To resolve this error, you need to contact the Data Source publisher or the Tableau Server administrator.
Change your Database
When you connect to data using Other Databases (JDBC) connectors, you specify the Database you are connecting with the JDBC connection string in the URL field. After connecting, if you want to change it to another Database, you have to edit the connection string or add a new connection with a new string. If you do not add the connection, you will get the below error.
- Error in Tableau Prep Builder
Tableau offers limited customer support for connections using Other Databases (JDBC) connectors.
Using Custom JDBC Driver with Tableau
The second method of establishing a Tableau JDBC integration is via custom drivers. Custom JDBC drivers are used with Business intelligence (BI) tools like Tableau and Power BI. You need to have an ODBC connection with JDBC drivers to use such BI tools. The ODBC connection is made to access and retrieve data into Tableau extract. Progress DataDirect SequeLink is an API that allows you to get ODBC access for your JDBC driver or JDBC access for your ODBC driver.
In this tutorial, you will learn to establish an ODBC connection for your JDBC driver. Progress DataDirect SequeLink has two components: a Server and a Client component. You will be using a JDBC Socket for the server and an ODBC client to access the JDBC driver with an ODBC connection. Let’s get started.
Prerequisites
- Windows 7 64-bit
- JDK 1.8 32 bit
Download and Installation
We will use Stocks-AlphaVantage API, a custom JDBC driver, for Tableau JDBC integration. You can read more about building your JDBC driver. Follow the below steps to use a custom JDBC driver with Tableau.
- Visit the Progress DataDirect SqueLink page and click on “Download“.
- Add the credentials like First Name, Last Name, Company, Country, and more to register on DataDirect.
- After registering, go to the download page. Under the “Server for JDBC Socket” tab, download the “Server for Windows“.
- And under the “Client for ODBC” tab, Download 32-bit or 64-bit ODBC client for Windows.
- Extract the Server for JDBC Socket and run the setup.exe file to install the server.
- Select default and move to SequeLink Service for the “JDBC Socket Settings” window during installation, as shown below.
- Enter the details as mentioned below.
- J2RE Path:
C:Program Files (x86)Javajdk1.8.0_161jre
- Driver Class-Path:
<path>/<to>/<customJDBCDriver.jar>
- Driver Class Name:
<Your JDBC Driver Class Name>
- Connection URL:
<Your JDBC Connection URL>
- Click on “Next” and complete the installation process.
- Go to the “Start” menu and open the SequeLink Management Console Snap-in in the Management Console:
- Ensure that SLAgent60 and SLAgentJDBC60 are both running.
- You can modify any configuration for the JDBC driver by changing the settings to general with SLSocketJDBC60 → Data Source Settings → Default → General.
- You can change the classpath for the driver using SLSocketJDBC60 → Service Settings → Environment.
Use the knowledgebase document if the service does not start JVM due to less memory.
- Install the SequeLink ODBC client you have downloaded in step 3. Extract the downloaded file and run the setup.exe file to install the SequeLink ODBC driver.
Configure ODBC Client
Follow the below steps to configure the ODBC Client.
- Open the installed ODBC administrator and click on the “Add” tab. Choose DataDirect SequeLink 6.0 as the driver, as shown below.
- Fill in the details as mentioned in the below image. Go to SLSocketJDBC60 → Service Settings → General to know the port where SequeLink JDBC Socket is running.
- By clicking on the Test Connect tab, you are connected with ODBC. You’re now all set to make the Tableau JDBC connection.
Connect with Tableau
You can connect Tableau with the above-created ODBC Data Source through your created JDBC driver. Progress DataDirect can be used with any JDBC driver and make it accessible as an ODBC connection for any user application.
That’s it, this is how you can easily set up a Tableau JDBC connection.
Read More About:
Connect MySQL to Tableau
Conclusion
With Tableau, you can access different data from Amazon Redshift, Amazon Athena, JSON files, Google BigQuery, Google Ads, and many more. Databases like PostgreSQL, SQL, MySQL, and more act as data sources for Tableau. With the Tableau JDBC integration, you can also explore customizing the JDBC drivers.
In this tutorial, you have learned to establish a Tableau JDBC connection using the Progress DataDirect driver and JDBC connector. Tableau makes Business Analysis more efficient through intuitive, interactive, and easy-to-use services. Moreover, analyzing and visualizing your data by loading it into a Data Warehouse from Tableau can be cumbersome. This is where Hevo comes in.
Hevo Data with its strong integration with 150+ Sources & BI tools allows you to not only export data from sources & load data to the destinations, but also transform & enrich your data, & make it analysis-ready so that you can focus only on your key business needs and perform insightful analysis using BI tools such as Tableau.
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Share your experience of working with the Tableau JDBC connection in the comments section below.
FAQs
1. Does Tableau use JDBC?
No, Tableau does not natively use JDBC (Java Database Connectivity). Tableau primarily uses ODBC (Open Database Connectivity) or its own native connectors to connect to databases. However, you can use JDBC with Tableau through a custom connector or if you set up an ODBC driver that internally uses JDBC.
2. Does Tableau use ODBC?
Yes, Tableau does use ODBC. It supports ODBC as one of the primary methods to connect to various databases and data sources, especially when there isn’t a native connector available. ODBC drivers are commonly used to interface Tableau with non-relational databases or other data systems.
3. Does Tableau use Java?
While Tableau itself is not built using Java, it does have some components and features that interact with Java. For example, Tableau’s extension framework supports JavaScript, and Java can be used in certain custom integrations or for writing Tableau Server automation scripts. But overall, Java is not a core part of Tableau’s architecture.
Manjiri is a proficient technical writer and a data science enthusiast. She holds an M.Tech degree and leverages the knowledge acquired through that to write insightful content on AI, ML, and data engineering concepts. She enjoys breaking down the complex topics of data integration and other challenges in data engineering to help data professionals solve their everyday problems.
