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Experimental Merge queries are available to design partners behind the merge-queries feature flag, and the flow, limits and wording on this page may change between releases. Contact Lightdash support to enable it for your organization. What Experimental means.
A merge query puts two explores side by side in one result. You pick the fields you want from each explore, say which field lines them up, and run. The merged result behaves like any other chart: you can configure it, save it, add it to dashboards, schedule it, and filter it from a dashboard. Use it when a question spans two explores that share a field at the same grain, such as review sentiment next to return rates for the same product, or orders next to payments for the same month.
Screen recording of adding a second explore to a query, choosing the join field and running the merged query

Merging Orders with Payments by month, from an explore to merged results

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Before you start

Each side of a merge is a normal explore query with its own metrics, dimensions and filters. Both explores must be in the same project. You need:
  • A shared field. A dimension that exists on both sides with matching values, such as a product code or a month. This becomes the join key. A merge can join on more than one field.
  • Matching grain. Every dimension you select from a side must be one of the join keys. This keeps each side to one row per key, so the join never multiplies rows. See how the join stays honest.
Anyone who can run queries in the explore can merge. There is nothing to install and no change to your dbt project.

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Merge two explores

1

Build the first side as usual

Open an explore and pick the fields you want from it. Filters you add here apply to this side only.
The Orders explore with Order date month and Total order amount selectedThe Orders explore with Order date month and Total order amount selected
2

Choose Merge another query

Open the query options menu, the ··· button next to the explore name at the top of the field panel, and choose Merge another query.
The query options menu with the Merge another query itemThe query options menu with the Merge another query item
3

Choose the second explore

The field panel switches to a Data sources view. Your first explore is listed with its selected fields, and a new card asks you to choose data to combine. Search the table list and pick the second explore.
The Data sources panel listing Orders and a Choose data to combine card above a searchable table listThe Data sources panel listing Orders and a Choose data to combine card above a searchable table list
4

Pick fields from the second side

You see the second explore’s field tree. Add at least one metric. The Relationship card tells you what is still missing.
Payments chosen as the second source, with the Relationship card asking for at least one metric from PaymentsPayments chosen as the second source, with the Relationship card asking for at least one metric from Payments
5

Set the join field on each side

In the Relationship card, each side has a field picker that offers dimensions only. The first side is prefilled with the dimension you already selected. Choose the matching field on the second side. Use Add join condition when the sides match on more than one field.
The Payments join field picker open, offering Order date monthThe Payments join field picker open, offering Order date month
6

Choose the join type

The summary next to Relationship reads the join back in words. The default is a full outer join. See which join type to choose.
The Relationship card with both join fields set to Order date month and the Left join type selectedThe Relationship card with both join fields set to Order date month and the Left join type selected
7

Run the query

Results arrive as one table. The join key has a key icon, and every other column carries the name of the explore it came from. Configure the chart the way you would for any explore.
Merged results with Order date month, Total order amount from Orders and Unique payment count from PaymentsMerged results with Order date month, Total order amount from Orders and Unique payment count from Payments
8

Save the chart

Save chart works as it does for any chart. The saved chart shows the relationship at the top and can be added to dashboards and scheduled deliveries.
A saved merged chart with a header reading Orders + Payments, matched on Order date monthA saved merged chart with a header reading Orders + Payments, matched on Order date month

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Which join type to choose

The three options answer one question: when a key exists on only one side, what happens to it?

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How the join stays honest

A merge is only safe when each side has exactly one row per join key. Because an explore query groups by its dimensions, that comes down to one rule: every dimension you select on a side must be a join key. Metrics are already one value per key, so any number of them is fine. When a selection breaks the rule, the query refuses with a message rather than multiplying rows. Either add that dimension as another join condition on both sides, or remove it. For example, reviews by product merged with returns by product, joined on product, works. Reviews by product and month merged with returns by product, joined on product only, refuses, because the review side has many rows per product. Add month to both sides and to the join conditions and it works again.

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Filters

Filters on either side apply to that side before the join. A dashboard filter on a merged chart is pushed into both sides, so a date filter narrows both explores rather than only the merged output.

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Current limits