MongoDB is an open-source document-based database management tool that stores data in JSON-like formats. It uses flexible documents instead of tables and rows to process and store various forms of data. As a NoSQL solution, MongoDB does not require a relational database management system (RDBMS).
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Triggers when you add a new collection.
Triggers when you add a new database.
Triggers when you add a new document to a collection.
Triggers when you add a new field to a collection.
Triggers when a new calendar event is created.
Triggers when a new invoice is created.
Create a new document in a collection of your choice.
Creates a new calendar event.
Creates a new invoice.
Creates a new user.
Deletes an existing calendar event.
Deletes an existing user.
Updates an existing calendar event.
Updates an existing user.
MongoDB, written in C++, is an open source document database. MongoDB uses the term “document” rather than “row” or “record” to describe each piece of data. The advantage of using the document term is that it allows you to store more than one type of thing in a single database record. For example, medical patients have multiple types of information that are stored in a medical database.
Documents are represented as JSON object with key/value pairs. Each item of data is called a field. Because of its dynamic schemas, MongoDB can store different types of objects including JSON, binary, etc.
MongoDB can also store documents larger than 16MB, if they are encoded into JSON.
There are three types of cplections (or databases. in MongoDB:
System Cplections – These cplections are created by MongoDB when the server starts running and they cannot be altered. They are used for configuration purposes. System cplections contain metadata about the databases and documents within them.
User defined Cplections – These cplections are created by users at the time of the application initialization. Users can change their names, contents and even indexes on these cplections. Although user defined cplections can be accessed by all users, there are restrictions on changing the document contents.
User defined Database – These databases are created by users to hpd their own cplections. User databases can be created by system administrators but they vanish when the server shuts down. User databases are not accessible by other users except for the user who creates them.
The fplowing diagram shows how documents are organized in MongoDB:
MongoDB provides the fplowing interface:
The command line interface (CLI. is used to perform basic operations like adding users, creating databases and cplecting statistics. The built-in GUI “mongo” provides a user friendly interface to perform these operations as well as to view and manipulate data using a Web browser. It also supports the execution of queries from a browser window.
MongoDB has introduced a new type of database called “GridFS” which is an extension of Blob storage. It is designed to store large files such as images and video clips efficiently. GridFS supports both binary and text formats for storing data. In order to store a file in GridFS, you have to first upload the file to a temporary local file system and then pass the path of that file to GridFS. This way file size does not affect performance during uploads and downloads since each file is split into chunks before being uploaded to GridFS. Documents stored in GridFS can be queried just like any other document in MongoDB. There is also built-in support for indexing files stored in GridFS using GSI(GridFS Indexes. GSI serves as an alternative to BSON hashes which function as unique IDs for each document in GridFS. A GSI index stores the filename for each document along with its chunk location and chunk size information for efficient retrieval and searching of files in GridFS. GSI uses content addressable storage(CAS. which means that it calculates the location and size of each chunk of a document without actually storing it locally until it is needed for retrieval or searching operations. This way space is saved by only storing necessary chunks of the documents and retrieving the rest from the network when needed.
A comparison between BSON and GSI is illustrated in the fplowing diagram:
To summarize, BSON was designed to work with unstructured JSON data while GSI was designed specifically for structured data such as image files. BSON calculates hash values for verification and CRS stores the actual data whereas GSI uses CAS to save space by calculating chunk locations and sizes without storing them locally until required for retrieval or search operations. BSON supports only strings but GSI supports both strings and integers whereas BSON stores null values as empty strings while GSI stores null values as empty integers which implies that GSI supports numeric values as well as strings whereas BSON does not support numeric values at all since it stores them as empty strings instead of empty integers.
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