Tableau BI tool is capable of connecting to a variety of data sources that can be a file system such as Excel, CSV, the relational database systems such as SQL Server, Oracle databases, DB2 database, the Cloud systems such as Google BigQuery, Windows Azure or through the other Data Sources such as ODBC connection.
Tableau Data Sources List
The following is the list of Data Sources that are supported by Tableau.
| Tableau Data Sources Types | ||
|---|---|---|
| Actian Matrix* | IBM DB2 9.1 or later for z/OS, Linux, or Windows (available on Tableau Desktop on Windows only) | Oracle Hyperion Essbase* |
| Actian Vector 2.0 or later* | IBM PDA Netezza 4.6 or later*,IBM BigInsights* | |
| Alibaba AnalyticDB for MySQL | Impala | Pivotal Greenplum 4.x or later |
| Alibaba Data Lake Analytics | JSON files | PostgreSQL |
| Alibaba MaxCompute | Kognitio | Presto |
| Amazon Athena | Kyvos | Progress OpenEdge 10.2B patch 4 or later* |
| Amazon Aurora | LinkedIn Sales Navigator | Qubole |
| Amazon Elastic MapReduce | MapR Distribution for Apache Hadoop 2.x or later | QuickBooks Online |
| Amazon Redshift | MariaDB | Salesforce.com, including Force.com and Database.com |
| Anaplan | Marketo | SAP HANA 1.0035 or later |
| Apache Drill | MarkLogic 7.0 and 8.0* | SAP NetWeaver Business Warehouse 7.00 with SP20+ recommended; also requires SAP GUI for Windows 7.20 or later client* |
| Aster Database | SingleStore (MemSQL) | SAP Sybase ASE 15.7 or later* |
| Box | Microsoft Access 2007 or later* | SAP Sybase IQ 16 or later* |
| TIBCO® Data Virtualization | Microsoft Azure Synapse (incl. Azure Active Directory support) | ServiceNow ITSM |
| Cloudera Hadoop Hive and Impala; Hive CDH3u1, which includes Hive .71, or later; Impala 1.0 or later (incl. Kerberos support for Impala) | Microsoft Azure SQL DB (incl. Azure Active Directory support) | Snowflake |
| Databricks (incl. Azure Active Directory support) | Microsoft Azure Data Lake Gen 2 | Spark SQL requires Apache Spark 1.2.1 or later |
| Datorama | Microsoft Excel 2007 or later | Spatial files (Esri Shapefiles, KML, GeoJSON, and MapInfo file types) |
| Denodo | Microsoft OneDrive | Splunk Enterprise 6 or later* |
| Dropbox | Microsoft PowerPivot 2008 or later* | Statistical Files; SAS (*.sas7bdat), SPSS (*.sav), and R (*.rdata, *.rda) |
| Esri ArcGIS Server | Microsoft SharePoint Lists, default list view only | Tableau Data Extract |
| EXASOL 4.2 or later | Microsoft Spark on HDInsight | Teradata 15.00.00 or later |
| Firebird 2.1.4 or later | Microsoft SQL Server 2005 or later (incl. support for Kerberos) | Teradata OLAP Connector 14.10 or later* |
| Google Ads | Microsoft SQL Server Analysis Services 2005 or later, non-tabular mode only*(incl. support for Kerberos) | Text files -- comma-separated value (.csv) files |
| Google Analytics | Microsoft SQL Server PDW V2 or later | Additional databases and applications that are ODBC 3.0 compliant |
| Google BigQuery | MonetDB | Tons of web data with the Web Data Connector |
| Google Cloud SQL | MongoDB BI | OData |
| Google Sheets | MySQL 5.5 or later | Oracle Database 11g Release 2 or later |
| Hortonworks Hadoop Hive 1.1 or later | HP Vertica 8.1 or later | Oracle Eloqua |
Tableau Data Sources Connection Feature
Tableau provides the different ways to make a connection with the Data Sources that dependents upon the requirement. For example, we can make a live connection with the data source to pull the data, or we can pull the data from the source system and put that in the memory or we can pull the data from various data sources and combine it and use it for data blending.
Let us see the Tableau Data Sources Connection Feature.
Tableau Live Connection
In the Tableau Live Connection feature, we can connect to the source system in real-time and do the data analysis. In Live connection, we can get the real-time changes that are done on the Source system. On the other side, the burden will be high on the Source System because it will have to send the data continuously to Tableau.
Tableau In Memory
In the Tableau In-Memory feature, Tableau fetches the data from the source system and puts them in memory for analyzing the data. The memory will depend upon the size which is available at that time.
Multiple Data Sources
The Data Blending feature of Tableau is used to connect the multiple data sources from a single sheet. We can connect from a file system and a relational database by setting up multiple connections.