Collection Tab

The Collection Tab shows the contents of a MongoDB collection. It’s made up of the Visual Query Builder, the Main Query Bar, the Results Tab, the Results Tab Toolbar, the Query Code tab, and the Explain tab.

In the above screenshot, Customers is a collection whose documents are shown in the Collection Tab, indicated by the green border. Download the Customers collection to follow along the tutorial.

Visual Query Builder

The Visual Query Builder lets users create MongoDB queries via drag and drop. Simply drag the desired field(s) to the query builder, drop it, set the operators, and run the query. It supports all MongoDB operators and field values.

As the query is built in the Visual Query Builder, the equivalent query will be displayed in the Main Query Bar in the mongo shell syntax

Main Query Bar

The Main Query Bar mirrors the query being built in the Visual Query Builder in JSON format which users can edit. It includes the Query, Projection, Sort, Skip, and Limit fields.

This tool is especially useful for the experienced developer, but also helps new users gain familiarity with reading and using JSON to build queries.

The Query Bar supports four short-hand query options to search by _id:

• ObjectId (either single or double quoted). If the user enters

57d28452ed5d4d54e8686f9d

into the query text field, it will be auto-expanded to

{ "_id" : ObjectId("57d28452ed5d4d54e8686f9d") }

• UUID (either single or double quoted). If the user enters

C37E3CBA-8FAF-4923-818A-09D92AB56182

into the query text field, it will be auto-expanded to

{ "_id" : UUID("C37E3CBA-8FAF-4923-818A-09D92AB56182") }

• Integer. If the user enters

9876543210

into the query text field, it will be auto-expanded to

{ "_id" : 9876543210 }

• A single or doubled quoted string. If the user enters

"2020-12-12"

into the query text field, it will be auto-expanded to

{ "_id" : "2020-12-12" }

The Query JSON Editor (“Multi-line Editor Tool”)

While the Main Query Bar only shows parts of a query, the Query JSON Editor displays the entire query in JSON. Here users can edit queries exactly how it would be done in the mongo shell.

To open the Query JSON Editor, click the button to the left of the ‘play’ symbol in the Main Query Bar.

The Run Query Button (“Play”)

Sitting directly to the right of the Query JSON Editor button, the Run (‘Play’) button runs the query on the respective collection. Additionally, this button contains a dropdown menu housing two other operations:

• “findOne(..)” – returns a single entry matching query
• “count(…)”. – will return the number of documents matching the query

Next to the Run button you’ll find a broom icon in the Query Bar. This will clear the query, projection, sort, skip, and limit parameters in one click.

Just above the Run Query and Query JSON Editor buttons are three additional buttons: Search Query History, Bookmark Query Manager,  and Copy Query to Clipboard.

Search Query History

Shows all previous that have been run. Queries are shown in JSON view.

Bookmark Query Manager

Saves oft-used queries and eliminates the need to repeatedly enter queries manually.

Copy Query to Clipboard

Copies the query automatically to the users’ clipboard.

Results Tab

The Results Tab offers three different options to view results and edit data: Tree View, Table View, and JSON View.

Tree View

Tree View allows for users to see the hierarchies in the data. Additionally, data can be edited in-place. Read more about Tree View.

Table View

Table View sorts data into columns and rows similar to a spreadsheet and enables custom views of embedded fields and sub-fields. As with Tree View, in-place editing is also available. Find full documentation of Table View here.

JSON View

JSON View shows the data as JSON documents.

Drag-and-drop query building is not available while in JSON View. However, for fast in-place editing, select the target value and Cmd-J will bring up the JSON editor panel. Read about JSON view here.

In-Place Data Editing

In-place editing is available throughout Studio 3T.  All three views – Table, Tree, and JSON – allow for data editing in real-time.

In Tree and Table View, this is done by double-clicking on any field. Additionally, a multi-line editor can be opened by clicking on the ellipsis icon.

In JSON View, right-click anywhere in the Results Tab and choose Document > Edit Document. This will open the Document JSON Editor.

The Results Tab Toolbar

Update Dialog

The Update Dialog is a pop-up editor within the Collection Tab that allows you to modify several documents at once. It is equivalent to the db.collection.updateMany() command in MongoDB.

To access the Update Dialog, right-click on any cell in Table View or Tree View and choose Update Dialog.

It has two tabs: Query and Update.

The Query tab is where you write the query to find the documents you want to update.

You can choose to apply one of three predefined queries (all documents in the collection, selected documents in the collection, or the current results from the Collection View), but you can customize the query as needed in the editor.

The Update tab is where you write the command that you want to run against your target documents, which you defined in the Query tab.

Once done, click Validate JSON to debug, and click Update to finalize.

Query Code

The Query Code tab allows user to convert queries into several different languages. The copy query to clipboard button will copy the code in the target language, thus allowing users to paste driver code easily into their desired application. Currently the languages supported are: mongo Shell, JavaScript (Node.js), Java (2.x driver API), Java (3.x driver API), C#, and Python.

Explain Tab

The Explain tab is one of the most powerful methods of fine-tuning query performance – it reveals how the query executes at the line level.

Older Studio 3T versions showed the query plan and execution statistics in this tree view:

With the release of Studio 3T 2018.6 came Visual Explain, a feature which outlines the same information in an easier-to-follow diagram format.

Learn more about Visual Explain in full here, and how you can use it to optimize MongoDB query performance.