This inherent incompatibility makes visualizing MongoDB data in traditional BI tools challenging, as it requires transforming the data to relational format.īelow, we’ll explore typical approaches to transforming MongoDB data and assess some of the more popular BI visualization tools. In contrast, MongoDB came to prominence only in the current decade and at its core is a NoSQL database that stores data in flexible, JSON-like documents. Popular BI Tools like Tableau and Qlik were introduced in the early 2000’s and 1990’s respectively, and were architecturally built to work with structured (tabular) data from traditional SQL data sources. Visualize Geospatial Data With MongoDB Compass (Source – ) Visualization Solutions for MongoDB With Compass, you can construct sophisticated queries on this data and execute them with a few clicks and a push of a button, which will then display your results both graphically and as a set of JSON documents. In MongoDB, you can store geospatial data as GeoJSON objects or as legacy coordinate pairs. In addition to exploring data in a visual environment, you can also use Compass to optimize query performance, manage indexes, and implement document validation.Īmong its notable features is its built-in schema visualization, which displays the structures of your collections and allows you to quickly visualize and explore your schema to understand the frequency, types and ranges of fields in your data set through an intuitive GUI.įor a look at how MongoDB and MySQL compare, check out our other blog post: MongoDB vs SQL MongoDB Compass Displays the Structure and Schema of Collections (Source – )Īnother feature is its ability to visualize geo-spatial data. Compass allows you to analyze and understand the contents of the data in your Mongo DB database without formal knowledge of MongoDB query syntax. MongoDB Compass is a stand-alone application and the go-to GUI tool for MongoDB, much like MySQL Workbench is MySQL’s associated tool. Use Data Explorer to View Data in MongoDB Atlas Cluster (Source – )ĭata Explorer makes it easy to perform actions on your data, allowing for even faster deployment of your Atlas clusters. Create and run aggregation pipelines to process your data.Create and drop databases, collections, and indexes. View databases, collections, and indexes in your cluster.Specifically, Data Explorer in Atlas allows you to: It comes with full CRUD functionality and allows you to query, explore, and take action on data residing inside your MongoDB Atlas cluster right from your web browser. MongoDB Data Explorer is a powerful feature available only in MongoDB Atlas. While useful, keep in mind that these are merely GUI tools that allow you to visually interact with your data and not meant for more meaningful visualizations. MongoDB’s Data Explorer Toolsįirst, we’ll discuss MongoDB’s explorer tools MongoDB Data Explorer and MongoDB Compass. In this post, we’ll provide an overview of existing visualization tools for performing and visualizing MongoDB analytics, including MongoDB’s own data explorer tools, traditional BI tools, and native solutions like MongoDB Charts and Knowi. It’s one thing to find a home for your data, it’s another thing to be able to understand it and put it to use. In the first part of our MongoDB series, we provided an overview of MongoDB Atlas, MongoDB’s cloud-based, open-source, NoSQL database offered as a fully managed DBaaS. Use an Open Database Connectivity (ODBC) Data Connector.Transforming MongoDB Data for Use In Standard BI Tools.You can also set up a 15-minute call with a member of our team to see if Knowi may be a good BI solution for your project. Want to skip ahead and get a Mongo BI solution launched? Check out our MongoDB Analytics page where you can start a Knowi trial.
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