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Introduction to MongoDB and Studio 3T
MongoDB is a document database, which is a type of NoSQL database that stores data as individual documents. This document database model provides the flexibility necessary to accommodate varying and evolving data structures, unlike the more rigid model seen in SQL or relational database management systems such as Oracle Database or MySQL. MongoDB is an […]
Connecting to MongoDB
This section walks you through the process of connecting to your existing MongoDB database, or the MongoDB Atlas cluster you created in Setting Up MongoDB Atlas, via Studio 3T. Studio 3T is available in three editions: Basic, Pro, and Ultimate. Basic has the essential features for working with MongoDB. Pro extends the features to include […]
The MongoDB Basics: Databases, Collections & Documents
To understand the MongoDB basics, we need to look at how data is stored in MongoDB. Data in MongoDB is made up of three types of components: databases, collections, and documents. The database sits at the top of the hierarchy, collections at the next level, and documents at the bottom. A database provides a container […]
Running MongoDB Queries on the mongo Shell
IntelliShell is a command-line tool built into Studio 3T that allows writing commands directly against a MongoDB database. It offers the simplicity of the mongo shell, which is what the tool is based on, while adding a number of important features that make it easier to query a database. For example, you can run commands individually, run multiple […]
Importing and Exporting MongoDB Data
Studio 3T greatly simplifies the process of importing and exporting MongoDB data. It provides the Import Wizard for retrieving document data from different sources, including .json files, .csv files, mongodump folders and archives, and other MongoDB collections. Most tasks within the wizard are simple point-and-click operations that control the source and target parameters for importing data. For […]
Using SQL in MongoDB Aggregation
In MongoDB, you can create aggregate queries that group data into meaningful categories of consolidated information, similar to aggregating data in a SQL or relational database. However, aggregation in MongoDB differs from SQL in several important ways, and if you’re new to MongoDB, these differences might seem confusing at first. Aggregation in MongoDB The process […]
Performing MongoDB CRUD Operations
One of the most common operations you’ll perform when working with MongoDB is querying document data. The better you understand how to retrieve data, the more effectively you can access the information you need – when you need it. Querying data is part of a larger set of operations commonly referred to as CRUD (Create, […]
Building MongoDB find() Queries
A MongoDB database stores data in collections. Each collection contains a set of related documents that are used by one or more applications to carry out their operations. The applications—as well as individuals managing the collections—must be able to query the data as efficiently as possible to ensure that the appropriate information is available whenever […]
Working with the MongoDB Aggregation Pipeline
The ability to aggregate data is essential to mining valuable information from a dataset. Aggregation can help you better understand the data, uncover patterns and trends that might not be readily apparent, and make strategic business decisions based on your findings. For this reason, most database management systems provide mechanisms for aggregating data. MongoDB is […]
Querying Arrays Using MongoDB $elemMatch
Documents in a MongoDB database commonly include fields defined with the Array data type. A field configured with this type can contain zero or more elements that together form a list—or array—of values. The values might all be the same data type, or they might be different types. For example, an Array field might contain […]