How Relationships Differ from Joins

Applies to: Tableau Cloud, Tableau Desktop, Tableau Server

Relationships are a dynamic, flexible way to combine data from multiple tables for analysis. You don’t define join types for relationships, so you won’t see a Venn diagram when you create them.

Think of a relationship as a contract between two tables. When you are building a viz with fields from these tables, Tableau brings in data from these tables using that contract to build a query with the appropriate joins.

  • No up-front join type. You only need to select matching fields to define a relationship (no join types). Tableau first attempts to create the relationship based on existing key constraints and matching field names. You can then check to ensure they are the fields you want to use, or add more field pairs to better define how the tables should be related.
  • Automatic and context-aware. Relationships defer joins to the time and context of analysis. Tableau automatically selects join types based on the fields being used in the visualization. During analysis, Tableau adjusts join types intelligently and preserves the native level of detail in your data. You can see aggregations at the level of detail of the fields in your viz rather than having to think about the underlying joins. You don't need to use LOD expressions such as FIXED to deduplicate data in related tables.
  • Flexible. Relationships can be many-to-many and support full outer joins. When you combine tables using relationships, it’s like creating a custom, flexible data source for every viz, all in a single data source for the workbook. Because Tableau queries only tables that are needed based on fields and filters in a viz, you can build a data source that can be used for a variety of analytic flows.

For more information, see Relate Your Data(Link opens in a new window) and Don’t Be Scared of Relationships.(Link opens in a new window)

Joins are still available as an option for combining your data. Double-click a logical table to go to the join canvas. For more information, see Where did joins go?

Watch a video: For an introduction to using relationships in Tableau, see this 5-minute video.

Note: The interface for editing relationships shown in this video might differ slightly from the current release but has the same functionality.

Also see video podcasts on relationships from Action Analytics(Link opens in a new window), such as Why did Tableau Invent Relationships?(Link opens in a new window) Click "Video Podcast" in the Library(Link opens in a new window) to see more.

For related information about how relationship queries work, see these Tableau blog posts:

Characteristics of relationships and joins

Relationships are a dynamic, flexible way to combine data from multiple tables for analysis. We recommend using relationships as your first approach to combining your data because it makes data preparation and analysis easier and more intuitive. Use joins only when you absolutely need to(Link opens in a new window).

Here are some advantages to using relationships to combine tables:

  • Make your data source easier to define, change, and reuse.
  • Make it easier to analyze data across multiple tables at the correct level of detail (LOD).
  • Do not require the use of LOD expressions or LOD calculations for analysis at different levels of detail.
  • Only query data from tables with fields used in the current viz.

Relationships

  • Are displayed as flexible noodles between logical tables
  • Require you to select matching fields between two logical tables
  • Do not require you to select join types
  • Make all row and column data from related tables potentially available in the data source
  • Maintain each table's level of detail in the data source and during analysis
  • Create independent domains at multiple levels of detail. Tables aren't merged together in the data source.
  • During analysis, create the appropriate joins automatically, based on the fields in use.
  • Do not duplicate aggregate values (when Performance Options are set to Many-to-Many)
  • Keep unmatched measure values (when Performance Options are set to Some Records Match)

Joins

Joins are a more static way to combine data. Joins must be defined between physical tables up front, before analysis, and can’t be changed without impacting all sheets using that data source. Joined tables are always merged into a single table. As a result, sometimes joined data is missing unmatched values, or duplicates aggregated values.

  • Are displayed with Venn diagram icons between physical tables
  • Require you to select join types and join clauses
  • Joined physical tables are merged into a single logical table with a fixed combination of data
  • May drop unmatched measure values
  • May duplicate aggregate values when fields are at different levels of detail
  • Support scenarios that require a single table of data, such as extract filters and aggregation

Requirements for using relationships

  • When relating tables, the fields that define the relationships must have the same data type. Changing the data type in the Data Source page does not change this requirement. Tableau will still use the data type in the underlying database for queries.
  • You can't define relationships based on geographic fields.
  • Circular relationships aren't supported in the data model.
  • You can't define relationships between published data sources.
  • Dirty data in tables (i.e. tables that weren't created with a well-structured model in mind and contain a mix of measures and dimensions in multiple tables) can make multi-table analysis more complex.
  • Using data source filters will limit Tableau's ability to do join culling in the data. Join culling is a term for how Tableau simplifies queries by removing unnecessary joins.
  • Tables with a lot of unmatched values across relationships.
  • In versions 2020.2 through 2024.1: Interrelating multiple fact tables with multiple dimension tables (attempting to model shared or conformed dimensions). In version 2024.2 and later, you can use multi-fact relationships to address these cases. For more information, see Multi-fact analysis with relationships(Link opens in a new window) and About Multi-fact Relationship Data Models(Link opens in a new window).

Where did joins go?

You can still specify joins between tables in the physical layer of a data source. Double-click a logical table to go to the Join/Union canvas in the physical layer and add joins or unions.

Every top-level, logical table contains at least one physical table. Open a logical table to view, edit, or create joins between its physical tables. Right-click a logical table, and then click Open. Or, just double-click the table to open it.

When you create a data source, it has two layers. The top-level layer is the logical layer of the data source. You combine data between tables in the logical layer using relationships.

The next layer is the physical layer of the data source. You combine data between tables at the physical layer using joins. For more information, see Logical and physical tables in the data model(Link opens in a new window).

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