The new autoValue feature gives you more control over how you want to populate your select fields.

Now you can automatically populate your select fields from data from any collection across your databases.

After months of work in collaboration with AWS, we are thrilled to announce that Humongous now offers complete support for AWS DocumentDB! 🎉

DocumentDB users can now leverage our full suite of tools to improve their data-related workflows.

Let's go through some of the key features unlocked by this launch.

CRUD operations

Giving users the ability to create, view, update, and delete documents is the most fundamental aspect of a GUI, and we've worked really hard to make sure Humongous CRUD interface is powerful, yet simple and intuitive.

For example, we've made it very easy to configure how you display data in your collections so that even your non-technical teams (e.g. marketing, customer support) can use it intuitively.

Search

Finding the correct documents is almost always the first step in any data-related workflow. Do you want to update the status of some users? You gotta find them first! Humongous helps you quickly find what you're looking for using a keyword-based Search engine , and also gives you the full power of the MongoDB Query Language when you need it.

Access control & Permissions

Humongous comes with pre-defined roles to control which actions can your collaborators perform on your data. When that's not sufficient, you can create your own custom Roles with finer levels of granularity.

Additionally, in cases where you need to meet some regulatory compliance and standards, our Audit feature lets you monitor how your data is accessed, including details such as who accessed which collections and when.

Charts & Dashboards

Humongous lets you create lightweight and fast Dashboards for your DocumentDB collections. It gives you the comfort of a nice UI to interactively build your charts as well as the flexibility to switch to a fully fledged editor to write custom queries.

Query Editor / IDE

Ad-hoc analyses are more often than not what drives the most impact in businesses. Our Query Editor tool provides the flexibility you need to quickly get high-impact analyses from your data.

I hope you're as excited about this launch as we are. If you want to give it a try, head over to our Getting Started guide, and let us know what you think at hello@humongous.io.

I'm a big fan of the Tag widget. I use it every day when looking at logs or some other collections data. Unfortunately, up until now, clicking on a tag would use the search bar to filter down your collection, which means you couldn't use the search bar directly.

We fixed this by introducing Chips as a way to encapsulate queries without using the search bar.

Now, when you click on a Tag or a Reference widget, a chip corresponding to your widget's query will be added to the toolbar, leaving your search bar free for further filtering.

Having to adjust the date picker every time you navigate to a dashboard can be pretty frustrating, and wasteful at the same time. You navigate to a dashboard, it loads the data using whatever time period is selected at the moment. You select the time period you wanted in the first place and the charts refresh with data for that time period.

We've added a new feature that lets you configure a default time period for individual dashboards. To configure a default time period, click on Update Dashboard in the dashboard menu dropdown. Select a time period in the Default Time Period field and click on save.

Now every time you navigate to the dashboard, it will automatically use the default time period you picked instead of the one set in the date picker.

It can take a decent amount of effort to create a great dashboard, chart or collection. And sometimes, you want your subsequent dashboards, charts or collections to be derived from it. That's why we've added the ability to duplicate those assets to create new ones.

Duplicate a collection

Click on the dropdown menu of the collection you want to copy and click Duplicate.

Duplicate a dashboard

Click on the dropdown menu of the dashboard you want to copy and click Duplicate.

Duplicate a chart

Click on the dropdown menu of the chart you want to copy and click Duplicate.

The Numeric Formatter takes a number and formats it. By default it uses your local separator to display numbers above 999. In the US for example, it would be a comma separator (e.g. 4,294,967) whereas in France it would be a space separator (e.g. 4 294 967).

Additional formatters are also available such as the currency formatter for financial data, the compact formatter for big numbers, the percentages formatter, and the scientific numbers formatter.

In 2021, we received at least a hundred requests asking for dashboard sharing in Humongous. But because our main focus was improving the MongoDB GUI aspect of our platform, we continuously put the sharing feature in the backlog.

But Today, after a few months of work, I'm excited to finally say that you can share and collaboratively edit dashboards with your teammates 🎉.

The feature comes with three roles. Readers can only view the dashboards. Editors can update charts definitions, add new charts and rearrange them. And finally, Admins have the full power to rename or even delete dashboards.

This feature is just the beginning of a series of collaborative features we have planned, so stay tuned.

I spend at least an hour every day doing support for Humongous, and every day, there's at least one person asking for help to correctly write a query.

Even though I absolutely enjoy the conversations, I wish there was an easy way to share fully functional examples of MongoDB queries with a simple URL.

After a lot of unsuccessful digging for such a tool, we decided to build one. Welcome to the Humongous MongoDB Playground. 🤯

The project is still in infancy with many missing features, but our goal is clear: Create a place to effortlessly write and share MongoDB Snippets.

Let's see how it works.

The main window is composed of two panes.

The left pane is where you write your MongoDB queries.

The right pane contains:

• A tab with the content of your database that you can modify it at will.
• The output of your queries.

In our example, the initial content is a list of countries, with their demographic information as well as their language and capital city.

Let's filter the database by only french speaking countries.

Or we can filter by countries with less than 30M people.

We can also make changes to the database content and write our queries against it. Let's go with some soccer stuff ⚽️.

This is just the beginning. We plan on incrementally improve what we have until our vision is achieved. In the meantime, do not hesitate to send your feedback to info@humongous.io.

Up until now, we could only customize the table layout at the field level. But, we've started working on some cool collection level customization and the first one to roll out is the table layout density. You can now choose from a Comfortable density or a more Compact one.

If you search for a good MongoDB GUI on Google today, you'll probably end up with a dozen tools, most of which unfortunately defunct or unmaintained.

To save you time and effort, we've compiled a list of the most modern and actively maintained MongoDB GUI out there.

We focused on the commercial tools in this article as these are usually the ones that continuously get maintained over the years. However, we'll make a separate article about the free ones too.

This list had initially been compiled in 2021, and revised in 2023.

MongoDB Compass

MongoDB, Inc (The company behind MongoDB) has its own GUI called MongoDB Compass. It's free of use and available on all major platforms.

The strongest features of MongoDB Compass are:

• The ability to build queries interactively, with support for various operators to sample, sort and filter your data.
• The ability to add indexes directly from the app, and track down query performance issues using the visual explain plan.
• The ability to construct aggregation queries visually, and debugging the different phases the aggregation pipeline.

Try MongoDB Compass

Humongous.io

Humongous.io goes beyond the classic MongoDB GUI and offers a fully-fledged online admin interface creation tool.

The most notable features of Humongous.io are:

• The Widget system lets you customize how you want your data to be displayed. Widgets can also be used to pull data from reference collections (e.g. replacing ids with users' email addresses).
• Smart Filters can be used to create filters around your collections displayed as chips for quick access.
• The Collaboration Features let you set up the platform as an internal admin tool rather than a simple GUI. No need to share database credentials anymore. Invite colleagues directly from the app.
• It comes with a Charts and Dashboards creation tool to track your metrics.

Humongous is subscription-based, with the base plan starting at $19 / month and the startup plan at $49 / month.

Try Humongous

Studio 3T

Studio 3T is a cross-platform GUI for MongoDB owned by the 3T Software Labs.

The major feature differentiators of Studio 3T are the following :

• Similar to NoSQLBooster, Studio 3T lets you directly write SQL to query your database.
• The Tree View displays the data into expandable hierarchies, which is suitable for large and deeply nested documents.
• The Code Generation Tool is able to export queries in Node.js, Python, Java, C#, PHP and Ruby.
• The Data importer works with SQL databases and Oracle.

Studio 3T also has a subscription-based pricing, starting at $199 / year / user for the base subscription, $399 / year / user for the Pro plan, and $699 / year / user for the enterprise plan.

Try Studio 3T

NoSQLBooster

NoSQLBooster is a shell-centric GUI for MongoDB.

It has many interesting features, with the most notable outlined below:

• The SQL query builder lets you query your collections with the SQL query language.
• You can import Node.js modules like lodash or moment.js within the shell using the Shell extensions.
• The Log Parser allows you to filter and analyze your MongoDB logs.
• It also comes with a Visual Explain system that transforms MongoDB explain output into a hierarchical view, allowing for query tuning.

NoSQLBooster is a license-based software. Pay once, and the version you paid for is yours. Today, the personal license (single user) costs $119 / license, the commercial license (single user) $219 / license The corporate license includes unlimited users for $8000 / license.

Try NoSQLBooster

The export feature in the app used to systematically include all fields in exported documents. We recently shipped an improvement to fix that. You now have the ability to include only the fields you choose. See it in action below:

Our main product is a MongoDB GUI, and all of our internal tools and databases are MongoDB based. We live and breathe MongoDB, and because of that, we see all sorts of MongoDB tools and services released all year round.

This year, we’ve decided to share with you our 2020 pick of the top 3 MongoDB tools and services we use the most.

This is the part one of a three posts series.

Mongoose

Mongoose is an open source MongoDB ODM (Object Document Mapping) based on the native MongoDB nodejs API. It’s a complete framework that handles the entire lifecycle of your objects, from schema definition, to objects validation, to documents versioning.

Here's a list of the features we like the most :

Schema definition

Schema definition is probably our favorite feature of Mongoose. It lets you model your objects with type requirements, validations and default values.

Our code source is version controlled and we define our models in a single place. This combination makes it very trivial to have a bird eye view of our entire database at any given time.

We used to rely heavily on the validation feature up until recently, but we moved to an internal validation framework that does a multi-step validation from the entrypoint of all of our controllers to the end of the request pipeline.

Plugins

The Mongoose Plugin system is a way to share logic and capabilities between schemas. We use it extensively throughout our codebase. One trivial example is the use the timestamp plugin which adds a created_at and an updated_at fields to every models. Another example is an internal ACL plugin we use to handle access and permissions on all resources created through Mongoose.

Populate

joins across collections in MongoDB do not feel as natural as they do in relational databases. MongoDB introduced $lookup a few years ago, but it's not intuitive and still very limited.

Mongoose overcome those shortcomings with a concept called Populate.

Populate automatically replaces the specified paths in a document with documents from other collections.

Mongoose has a lot more to offer. Check out the documentation and especially don’t hesitate to sponsor if you like it.

This is it for part one of our top picks of MongoDB tools. If you liked it, follow us on Twitter @humongousio.

You normally have a list of collections on the left menu of HumongouS.io. They are just labels that you can change at will.

Instead of having them plain, you can prefix them with nice little emojis. Bonus is that they’re surprisingly effective at easing the quick scan process 😀.

Here’s a cool example :

Not remembering the names of your collections fields when you’re about to write a query can be very frustrating, that’s why we’ve added a new auto-completion feature in the Search bar.

It’s only phase 1 for this feature. We’ll iterate on it as we get more feedback and expand it to other places in the app that allow you to enter MongoDB queries (i.e Charts, Collection filters...).

We recently added a new Table option to duplicate data in your collections. In order to use it, first select the documents you would like to duplicate, click on More to open the Table options dropdown and click on Duplicate documents.

Being able to scroll and keep the table header fixed has been a paint point for many users for a long time. This issue has now been fixed (no pun intended :) ) in the latest release.

We’ve added a convenient button to directly copy long JSON data from the JSON view.

This is a long outstanding request that we just fulfilled. We couldn’t be happier. It’s now possible to re-order your charts by drag and dropping them. Yay!

Going from collection to collection very frequently can be quite tedious especially if you’re doing it across projects. You’ve asked it and we’ve listened. The next time you refresh your browser, type ⌘+J and jump from collection to collection at the speed of light.

We’ve made some improvements on the way we present the search bar on mobile. Only the current project title is shown on the header to create more space. The search bar will be accessible by clicking on the search button on the right hand side of the menu.

It is now possible to clone your existing charts. It’s super simple. Open the chart’s contextual menu and click on Clone and voilà!

Toolbar widgets are a new category of widgets. They add new features to your collections’ toolbar.

The first one we’ve released in the Quick filter toolbar. It gives you a way to have a list of predefined labeled queries in your collections.

When we launched our MongoDB dashboard creator, the only way to create new charts was by using our Visual Query Builder. Although this enabled quick prototyping for basic charts, it quickly showed its limitations, and you expressed your needs for something more powerful.

Today we're releasing Raw Query Builder. A new way to create charts using the MongoDB Query Language.

Using the Raw Query Builder is very simple. We've introduced a new tab, next to the Visual Query Builder that lets you select the new mode. Once you click on it, you'll see an code editor to type in your query.

Once you're done writing your query, click on the Run button to test it, and you should see the result directly in the chart on your right. We will also show you hints when there are some errors in your query, or even suggestions on how to fix it in some cases.

We're super excited about this feature, and we're eager to get your feedback and the coming weeks.

You can now use date presets like $date_yesterday or $date_3_weeks_ago to filter down your collections.

In case you need finer control over your collaborators roles, you can now create and assign custom roles.