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Blog › The Best MongoDB Visualization, Reporting and Analytics Tools [Updated
2024]
a


THE BEST MONGODB VISUALIZATION, REPORTING AND ANALYTICS TOOLS [UPDATED 2024]

Sherry Quach


Read this article to learn about choosing the best MongoDB visualization and
reporting tool for your team.


CHOOSING THE BEST MONGODB VISUALIZATION, REPORTING, AND ANALYTICS TOOL

In today’s data-driven world, businesses are becoming increasingly reliant on
accurate and efficient data analysis to drive decision making. As a result,
selecting the optimal BI tool or data platform is a critical decision. MongoDB,
a popular NoSQL database, is compatible with various BI tools and data
platforms, but determining the best suited tool for your organization’s needs is
not a trivial task. Continue reading for an in-depth comparison between some of
the top MongoDB data visualization tools on the market.

In this article, we will compare 5 of the best BI tools / data platforms for
analyzing MongoDB data:

 * MongoDB Charts
 * Tableau
 * Qlik
 * Knowi
 * and Looker.

To start, we will give a high level overview of each tool. We will then explore
each one’s ease of use, pricing model, data integration flow, customization
options, and functionality to help you make an informed decision. We will
conclude with a summary on what each tool is best for. The best tool for you
depends on your specific needs, budget, and technical skillset.


AN OVERVIEW OF THE BEST MONGODB VISUALIZATION TOOLS

Screenshot: Sample MongoDB Dashboard


MONGODB DASHBOARDS & DATA VISUALIZATION TOOLS: MONGODB CHARTS

MongoDB Charts is a native data visualization tool integrated within MongoDB. It
offers a way of natively visualizing MongoDB data, allowing you to create
interactive charts and dashboards without needing to move your data using
additional tools. Charts can be embedded directly into MongoDB applications or
shared with others.

Pros:

 * Already integrated with MongoDB data
 * Drag and drop builder

Cons:

 * Only supports MongoDB data
 * Doesn’t easily support cross-collection joins

Screenshot: Sample Looker Dashboard (source:
https://cloud.google.com/blog/products/data-analytics/new-looker-dashboards)


MONGODB DASHBOARDS & DATA VISUALIZATION TOOLS: LOOKER

Looker is a data visualization tool acquired by Google in 2019. Looker can
connect to BigQuery, Redshift, and many other SQL databases. It does require
tools to ETL your data from your data store into the platform. Aside from
dashboards and visualizations, Looker has many capabilities packed in including
embedding, actions, and data modeling.

Pros:

 * Lots of visualization options
 * Supports git version control

Cons:

 * Requires MongoDB connector and JDBC driver to pull data in
 * Requires learning LookML

GIF of Knowi Dashboard (source: knowi.com)


MONGODB DASHBOARDS & DATA VISUALIZATION TOOLS: KNOWI

Knowi is an all-in-one data analytics platform that makes analyzing MongoDB data
easy. What sets Knowi apart from the others is that you do not need to ETL/ELT
your data before querying or visualizing it. With its drag-and-drop builder and
Mongo Query Language support, it was designed to fit the needs of both technical
and non-technical users. It can connect into and join between SQL and NoSQL
databases (including MongoDB and MongoDB Atlas) as well as external applications
such as Salesforce, Quickbooks, and HubSpot.

Pros

 * Supports MongoDB and MongoDB Atlas natively without any additional
   tools/connectors
 * Seamlessly supports NoSQL/SQL data blending
 * Supports MongoDB Query Language natively

Cons

 * Limited ML Capabilities
 * May require query optimization with direct connections

Screenshot: Sample Tableau Dashboard (source:
https://www.tableau.com/data-insights/dashboard-showcase/superstore)


MONGODB DASHBOARDS & DATA VISUALIZATION TOOLS: TABLEAU

Tableau is a data visualization tool known for its aesthetics and simplicity,
enabling users to create visually appealing dashboards with minimal effort. It
supports a wide range of data sources and uses a drag and drop interface.
Tableau was built before data storage systems such as MongoDB were developed,
and as a result, best supports structured data.

Pros

 * Drag and drop interface
 * Chart types are visually appealing

Cons

 * Requires MongoDB connector and driver
 * Requires relational data

Screenshot: Sample Qlik Dashboard (Source:
https://www.qlik.com/us/dashboard-examples/dashboard-design)


MONGODB DASHBOARDS & DATA VISUALIZATION TOOLS: QLIK

Qlik is a data analytics tool known for its intuitive design for data
exploration, allowing users to discover insights via a visual builder. It offers
both a cloud and an on-premise version. Some features Qlik supports includes
reporting, dashboard and visualization building, embedding and more.

Pros

 * Good for data exploration
 * Generally user friendly

Cons

 * Requires MongoDB connector and driver
 * Steep learning curve for complex use cases


MONGODB REPORTING & DATA VISUALIZATION TOOLS: PROS & CONS COMPARISON GUIDE

ToolProsConsKnowi– Supports MongoDB and MongoDB Atlas natively
– Seamlessly supports NoSQL/SQL data blending
– Supports MongoDB Query Language natively– Limited ML capabilities
– May require query optimization with direct connectionsMongoDB Charts– Already
integrated with MongoDB data
– Drag and drop builder– Only supports MongoDB data
– Doesn’t easily support cross-collection joinsLooker– Lots of visualization
options
– Supports git version control– Requires MongoDB connector and JDBC driver to
pull data in
– Requires learning LookMLTableau– Drag and drop interface
– Chart types are visually appealing– Requires MongoDB connector and driver
– Requires relational dataQlik– Good for data exploration
– Generally user friendly– Requires MongoDB connector and driver
– Steep learning curve for complex use cases


MONGODB VISUALIZATION TOOLS: KEY CONSIDERATIONS COMPARED 

Next, we will dive into the following categories for each tool:

 * Ease of Use
 * Pricing
 * MongoDB Data Integration
 * Customization Options
 * Functionality


EASE OF USE COMPARISON BETWEEN MONGODB VISUALIZATION TOOLS:

ToolEase of UseMongoDB ChartsMongoDB Charts offers a seamless user experience by
leveraging the familiarity of the MongoDB ecosystem. It uses a drag-and-drop, no
code visual builder.LookerLooker allows users to build interactive dashboards
using LookML, making it suitable for more technical users.KnowiKnowi has a
user-friendly interface with intuitive drag-and-drop functionality, making it
accessible to users with varying levels of technical expertise. To build
visualizations, you can use the drag-and-drop builder, native Mongo Query
Language, and/or Cloud9QL (SQL-like syntax). It also supports using natural
language to retrieve a visualization.TableauTableau’s user interface is known
for its simplicity, enabling users to create visually appealing dashboards with
minimal effort through a drag-and-drop builder.QlikQlik’s drag-and-drop
interface and guided data exploration features make it relatively easy for users
to navigate and analyze MongoDB data. You can explore your data and find
connections and patterns without mapping any relationships in advance.


PRICING COMPARISON BETWEEN MONGODB VISUALIZATION TOOLS:

ToolPricingMongoDB ChartsMongoDB Charts is free to use for self-hosted
deployments and available as a paid add-on for MongoDB Atlas. Using MongoDB
Charts is free for up to approximately 500,000 chart renders per month, and up
to 1GB of data transferred. Beyond the first 1GB, it costs $1 per additional GB
of data transferred. *LookerLooker’s pricing is customizable based on factors
such as the number of users, data volumes, and required features. You must speak
with a sales representative to obtain pricing information. It does have a more
limited free version called Looker Studio.KnowiKnowi offers flexible pricing
options based on the number of users and features needed. There are three
different plans on the cloud hosted version as well as an on-premise deployment
option. One thing to factor in is that you do not need any ETL/ELT tools with
Knowi, cutting your overall data tool costs down.TableauTableau’s pricing
structure is tiered and can be costly for large-scale deployments, especially
when considering additional add-ons and data sources.QlikQlik’s pricing model
varies based on deployment type (cloud or on-premises) and user licenses, making
it suitable for both small and large organizations.

* From MongoDB’s pricing page: “In addition, any applicable Atlas data transfer
fees apply, as per the Data Transfer Fees section of the Atlas
Pricing page. Charts is hosted on AWS us-east-1 region, and uses this region to
calculate the fees.”


MONGODB DATA INTEGRATION COMPARISON BETWEEN MONGODB VISUALIZATION TOOLS:

ToolData IntegrationMongoDB ChartsBeing an official MongoDB tool, Charts
integrates seamlessly with MongoDB Atlas and provides native
connectivity.LookerLooker requires using a MongoDB connector and JDBC driver to
pull MongoDB data in.KnowiKnowi offers native connection to MongoDB and MongoDB
Atlas, no ETL/ELT tools or connectors required.TableauTableau requires a
connector to pull data from MongoDB and other data sources.QlikQlik requires
connectors to connect to MongoDB and other data sources.


CUSTOMIZATION OPTION COMPARISON BETWEEN MONGODB VISUALIZATION TOOLS:

ToolCustomizationMongoDB ChartsCharts offers limited customization options,
primarily focused on visual styling and branding, making it suitable for basic
analytics needs.LookerLooker offers significant customization options, including
custom visualizations and embedding capabilities, enabling users to build
tailored experiences.KnowiKnowi offers extensive customization options through
its widget and dashboard builder, enabling users to tailor their visualizations’
and reports’ look and feel.  TableauTableau provides a wide range of
customization options, allowing users to create highly interactive dashboards
and reports with advanced features.QlikQlik offers extensive customization
capabilities, empowering users to create personalized dashboards and
visualizations to suit their needs.


FUNCTIONALITY COMPARISON BETWEEN MONGODB VISUALIZATION TOOLS:

ToolFunctionalityMongoDB ChartsMongoDB Charts focuses on basic data
visualization and exploration, with limited advanced analytical
featuresLookerLooker offers robust analytics capabilities, including data
exploration, cohort analysis, and advanced calculations, allowing users to gain
valuable insights from their MongoDB data. It offers embedding, reporting,
machine learning capabilities, and more.KnowiKnowi provides advanced analytics
capabilities, including natural language insights, data forecasting, and natural
language querying, making it a robust choice for in-depth analysis. With Knowi,
you can embed, trigger alerts, send reports, share assets, create machine
learning models, and more.TableauTableau offers a broad range of analytics
features, including advanced calculations, statistical modeling, and predictive
analytics, making it a comprehensive data analysis toolQlikQlik provides
powerful data discovery features, associative analytics, and augmented
intelligence capabilities, making it suitable for complex data analysis
scenarios.


CONCLUSION – WHAT IS THE BEST MONGODB REPORTING TOOL FOR YOUR TEAM?

When analyzing MongoDB data, the choice of an analytics platform depends on your
specific use case. A tool’s ease of use, pricing, data integration process,
customization options, and functionality are all important deciding factors. 

Knowi stands out since it does not require ETL/ELT, can join between structured
and unstructured data, and supports MQL (Mongo Query Language) natively. MongoDB
Charts is a great option since you do not need to transport your data, and it is
free to start with usage-based pricing. (See the pricing section above for more
details.) Overall, MongoDB Charts is a great choice for basic use cases with a
low volume of data and chart loads. Tableau, Qlik, and Looker provide
comprehensive analytics capabilities with varying degrees of customization and
pricing models, but tend to end up being costly since they require connectors
and additional tools to move and translate your data. 

Understanding your organization’s needs, budget, and technical skillset will
help you select the most suitable tool to unlock the full potential of your
MongoDB data.


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About the Author:

SHERRY QUACH

Sherry is a Data Analyst at Knowi having previously worked at the California
Emerging Infections Program analyzing public health infectious disease data.
Sherry is skilled in data visualizations, SQL, data analysis, and business
intelligence. Sherry holds a BS, Molecular and Cellular Biology from University
of California, Berkeley and has contributed to research papers including
Characteristics and Maternal and Birth Outcomes of Hospitalized Pregnant Women
with Laboratory-Confirmed COVID-19 — COVID-NET, 13 States and
COVID-19–Associated Hospitalizations Among Health Care Personnel — COVID-NET, 13
States.
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