![]() Sharding distributes a single dataset across multiple databases. You can leverage tools like Performance Advisor to further understand which query could benefit from indexes. This would be much better than having one index on “Last name” and another on “First name”. If you’d want the first and last name to be returned, you can create an index that includes both “Last name” and “First name”. For example, say you’ve got several documents containing the employee’s first and last names in separate fields. You can use various indexing strategies, including compound indexes on multiple fields. Isn’t this far better than reading every document in the collection? Indexing saves time by scanning the index to limit the documents inspected. You can index any field in a MongoDB document to increase its efficiency and improve query speed. It also has several stages, like the Union stage, which flexibly puts together results from multiple collections. It’s flexible because it allows you to process, transform, and analyze data of any structure.īecause of this, MongoDB allows fast data flows and features across 150 operators and expressions. You can use this framework to club several operators and expressions. ![]() To view a list of the collections that belong to a database, use the command listCollections. Secondly, the documents needn’t be of the same data type! They’re similar to tables in relational databases.Ĭollections, however, are much more flexible. CollectionsĪ collection is a group of documents associated with one database. They also offer protection against downtime during a system failure or planned maintenance. These copies are known as “replica sets,” and they continuously replicate data between them, ensuring improved availability of your data. When you create a new database in MongoDB, the system automatically creates at least 2 more copies of your data. This ensures faster access and increased support for various data types like string, integer, boolean number, and much more! Replica Sets Additionally, MongoDB converts documents into a binary JSON (BSON) type. Fields in a JSON document can differ from document to document, so they won’t be added to every record in the database.ĭocuments can store structures like arrays that can be nested to express hierarchical relationships. That’s not the case with fields in a JSON document. ![]() In a relational database table, you must add a column to add a new field. The documents map naturally to the objects in the application code, making it more straightforward for developers to use. MongoDB has a document data model that stores data as JSON documents. This is why it’s preferred by companies like Google, Toyota, and Forbes.īelow, we’ll explore some key characteristics of MongoDB. MongoDB is also known for its speedy query execution. Did you know that NoSQL databases are actually faster than relational databases? This is due to characteristics like indexing, sharding, and aggregation pipelines.
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