MongoDB Analytics & Reporting
Build MongoDB reports and data visualization in real time with true native intergration.
Natively integrate to data sources like SQL, NoSQL (MongoDB, Elasticsearch, InfluxDB…), Rest API and cloud data sources
Plugin MongoDB Queries
Schema Discovery & MongoDB Query Generation
40+ visualizations to create dashboards that matter
Direct query execution into your database to drive visualizations, or, store and track seamlessly using our scalable, schema-less, flexible cloud warehouse
Auto-generate intutive dashboards or get instant insights with Knowi’s Private GPT.
Single Sign-On API for embedding inside your portal
Choose between Cloud or On-Prem deployment options
📆 Book your 30 minute demo
Phil Bryant
VP Business Intelligence, MacroFab
Hundreds of companies trust Knowi to unify their analytics
Business intelligence for MongoDB
A lot of BI tools offer stunning dashboards and visualizations but require your data to be confined to a strict structure and schema–making them useless for NoSQL data sources like MongoDB.
Knowi is different. Knowi was built from the ground up with the aim of providing a unified business intelligence solution for unstructured data like MongoDB.
Embedded analytics
Knowi can be embedded right into your application using an iframe or javascript. That means you can white-labeled Knowi as the analytics solution inside your product and sell its features as part of your GTM.
With powerful dashboards and reporting, users can get real-time analytics that will provide tangible value to your product offering. No ETL required. No additional hardware needed.
4 steps to connect your MongoDB data to Knowi
- Click “Add Connection”
- Select MongoDB from the Datasources
- Insert your Mongo connection credentials.
- Hit “Connect”
And that’s it. You’re now natively connected to your MongoDB data can now be used to create dashboards, visualizations, ad hoc reports, and more. Try a live MongoDB connection with Knowi.
How is Knowi different than the alternatives?
The three biggest options companies look at for MongoDB analytics are MongoDB Charts, using the Mongo BI Connector to get their data into one of the old guard BI tools like Tableau, or using ETL/ELT processes to move all their data into a relational data warehouse.
BI Connector
A lot of business intelligence tools like Tableau use the Mongo BI Connector. The problem here is that the BI Connector works by putting a SQL layer on top of Mongo, forcing your unstructured data into a relational structure, invalidating the entire point of using a NoSQL database. It’s a classic square peg in a round hole problem.
This solution can also add additional expenses through enterprise licensing and driver purchasing.
MongoDB Charts
ETL + Data Warehouse
The third option is to use ETL or ELT to apply a schema to all of your data and run regular migrations to a data warehouse. This suffers from the same square peg in a round hole problem where you are forcing schema on unstructured data. It also requires the build out of costly ETL pipelines and maintenance of data warehouse infrastructure.
Lastly, going this route often results in versioning issues, since the data your working with in your data warehouse is only as up-to-date as the last ETL process run.
Knowi avoids all of these issues because it was built from the ground up to support unstructured non-relational data. Knowi is built on data virtualization which enables true native integration that other business intelligence platforms simply cannot do.
Native MongoDB analytics
You simply connect Knowi to MongoDB and start writing queries. Knowi is the only complete BI solution that is fully native to MongoDB and supports nested objects and arrays. No ODBC drivers, no SQL layer in the middle, no pre-defined schemas, no ETL. No mess. No fuss.
Cross database joins
Join MongoDB data with NoSQL, Relational, RDBMS, and APIs on the fly across data centers or multiple cloud providers, eliminating costly ETL processes that move and SQL-ify your MongoDB data.
Search-based analytics
Transform how your company uses its data with the use of Google-search-like capabilities on top of MongoDB. Knowi's search-based analytics will enable your business users to perform ad-hoc analysis in real time.
MongoDB Reporting & Analytics
Welcome to the most powerful solution for analytics and visualization on MongoDB. Knowi is the only MongoDB BI provider that not only delivers truly native MongoDB visualization and reporting but also allows you to join disparate data sources. You can connect your MongoDB data with other relational data sources, NoSQL databases, and data from REST APIs. If that’s not enough, Knowi comes with integrated machine learning and search-based analytics for advanced business intelligence using MongoDB data.
Embedded Mongo Database Analytics
Build Data-Driven Applications: With just a few clicks, you can securely embed dashboards directly into your applications your business teams are already using. Users can also share MongoDB dashboards or email PDF reports to extend analytics reporting to offline users company wide.
Machine Learning
Combine hindsight and foresight with our machine learning workbench. Integrate machine learning directly into your MongoDB data analysis workflows. With Knowi ML, you can automatically trigger actions based on resulting calculations. You choose to integrate your custom algorithms or tap into our library of open source algorithms.
Triggers, Alerts, and Actions
Automate actions or notifications based on the results of your MongoDB analytics. Easily send notifications with data attached or invoke a webhook to initiate a process in a downstream application.
See our latest MongoDB Reporting and Visualization Tool Comparison Guide to know what solution can be best for your MongoDB analytics usecase
Frequently Asked Questions about MongoDB analytics and reporting
Knowi tends to be a great fit for the use cases that are too complex for MongoDB Charts. Some use cases work fine sticking to only MongoDB data, but there are also a lot of companies where Mongo is only one part of their data ecosystem. For these companies, being able to support a variety of NoSQL and SQL data sources and join data across databases is crucial. This is where Knowi is often a better fit.
Knowi also works well when companies need to be able to embed their analytics solution in their existing workspace, website, or app.
As with all applications, it depends on the use case itself. But Knowi's ability to do real-time analytics natively on MongoDB data can certainly power a lot of data science applications. Additionally, with Knowi, you can join across databases; meaning you can join your MongoDB data with data from relational databases. So if you have some unstructured data in MongoDB and some data in a structured SQL database, you can still do analytics.
Lastly, Knowi's ability to easily pull in data from REST APIs can be useful for pulling in data from outside sources for data science use case.