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    regarding mongodb, how do documents and collections compare to rows and tables in a relational database? which of the following statements regarding documents is accurate?


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    What is MongoDB? Features and how it works – TechTarget Definition

    Learn about MongoDB, how it works and is used. Explore features, pros /cons and the MongoDB platforms. This definition also covers how it compares to RSBMS.



    Alexander S. Gillis, Technical Writer and Editor

    Bridget Botelho, Editorial Director, News

    What is MongoDB?

    MongoDB is an open source NoSQL database management program. NoSQL (Not only SQL) is used as an alternative to traditional relational databases. NoSQL databases are quite useful for working with large sets of distributed data. MongoDB is a tool that can manage document-oriented information, store or retrieve information.

    MongoDB is used for high-volume data storage, helping organizations store large amounts of data while still performing rapidly. Organizations also use MongoDB for its ad-hoc queries, indexing, load balancing, aggregation, server-side JavaScript execution and other features.

    Structured Query Language (SQL) is a standardized programming language that is used to manage relational databases. SQL normalizes data as schemas and tables, and every table has a fixed structure.

    Instead of using tables and rows as in relational databases, as a NoSQL database, the MongoDB architecture is made up of collections and documents. Documents are made up of key-value pairs -- MongoDB's basic unit of data. Collections, the equivalent of SQL tables, contain document sets. MongoDB offers support for many programming languages, such as C, C++, C#, Go, Java, Python, Ruby and Swift.

    How does MongoDB work?

    MongoDB environments provide users with a server to create databases with MongoDB. MongoDB stores data as records that are made up of collections and documents.

    Documents contain the data the user wants to store in the MongoDB database. Documents are composed of field and value pairs. They are the basic unit of data in MongoDB. The documents are similar to JavaScript Object Notation (JSON) but use a variant called Binary JSON (BSON). The benefit of using BSON is that it accommodates more data types. The fields in these documents are like the columns in a relational database. Values contained can be a variety of data types, including other documents, arrays and arrays of documents, according to the MongoDB user manual. Documents will also incorporate a primary key as a unique identifier. A document's structure is changed by adding or deleting new or existing fields.

    Sets of documents are called collections, which function as the equivalent of relational database tables. Collections can contain any type of data, but the restriction is the data in a collection cannot be spread across different databases. Users of MongoDB can create multiple databases with multiple collections.

    The mongo shell is a standard component of the open-source distributions of MongoDB. Once MongoDB is installed, users connect the mongo shell to their running MongoDB instances. The mongo shell acts as an interactive JavaScript interface to MongoDB, which allows users to query or update data and conduct administrative operations.

    A binary representation of JSON-like documents is provided by the BSON document storage and data interchange format. Automatic sharding is another key feature that enables data in a MongoDB collection to be distributed across multiple systems for horizontal scalability, as data volumes and throughput requirements increase.

    The NoSQL DBMS uses a single master architecture for data consistency, with secondary databases that maintain copies of the primary database. Operations are automatically replicated to those secondary databases for automatic failover.

    MongoDB supporting technologies include MongoDB Stich, Atlas Global Clusters, and Mobile, along with newer MongoDB updates.

    Why is MongoDB used?

    An organization might want to use MongoDB for the following:

    Storage. MongoDB can store large structured and unstructured data volumes and is scalable vertically and horizontally. Indexes are used to improve search performance. Searches are also done by field, range and expression queries.Data integration. This integrates data for applications, including for hybrid and multi-cloud applications.Complex data structures descriptions. Document databases enable the embedding of documents to describe nested structures (a structure within a structure) and can tolerate variations in data.Load balancing. MongoDB can be used to run over multiple servers.

    Features of MongoDB

    Features of MongoDB include the following:

    Replication. A replica set is two or more MongoDB instances used to provide high availability. Replica sets are made of primary and secondary servers. The primary MongoDB server performs all the read and write operations, while the secondary replica keeps a copy of the data. If a primary replica fails, the secondary replica is then used.Scalability. MongoDB supports vertical and horizontal scaling. Vertical scaling works by adding more power to an existing machine, while horizontal scaling works by adding more machines to a user's resources.Load balancing. MongoDB handles load balancing without the need for a separate, dedicated load balancer, through either vertical or horizontal scaling.Schema-less. MongoDB is a schema-less database, which means the database can manage data without the need for a blueprint.Document. Data in MongoDB is stored in documents with key-value pairs instead of rows and columns, which makes the data more flexible when compared to SQL databases.

    स्रोत : www.techtarget.com

    What is a relational database?

    In this essential guide, learn about how relational databases work and how they compare to other database options.

    स्रोत : www.ibm.com

    Comparing The Differences

    Understand the differences between MongoDB and MySQL, the scalability and security options for each offering, and which database to use when.

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    MongoDB vs. MySQL Differences

    MongoDB vs. MySQL Differences What are the main differences between MongoDB and MySQL?


    MySQL is a popular, free-to-use, and open-source relational database management system (RDBMS) developed by Oracle. As with other relational systems, MySQL stores data using tables and rows, enforces referential integrity, and uses structured query language (SQL) for data access. When users need to retrieve data from a MySQL database, they must construct an SQL query that joins multiple tables together to create the view on the data they require.

    Database schemas and data models need to be defined ahead of time, and data must match this schema to be stored in the database. This rigid approach to storing data offers some degree of safety, but trades this for flexibility. If a new type or format of data needs to be stored in the database, schema migration must occur, which can become complex and expensive as the size of the database grows.


    MongoDB is also free to use and open source; however, its design principles differ from traditional relational systems. Often styled as a non-relational (or NoSQL) system, MongoDB adopts a significantly different approach to storing data, representing information as a series of JSON-like documents (actually stored as binary JSON, or BSON), as opposed to the table and row format of relational systems.

    MongoDB documents consist of a series of key/value pairs of varying types, including arrays and nested documents; however, the primary difference is that the structure of the key/value pairs in a given collection can vary from document to document. This more flexible approach is possible because documents are self-describing.

    When to use MongoDB vs. MySQL

    The core differences between these two database systems are significant. Choosing which one to use is really a question of approach rather than purely a technical decision.

    MySQL is a mature relational database system, offering a familiar database environment for experienced IT professionals.MongoDB is a well-established, non-relational database system offering improved flexibility and horizontal scalability, but at the cost of some safety features of relational databases, such as referential integrity.

    Which one should you choose?

    In the following sections, we’re going to look at some of the different considerations when deciding between MongoDB and MySQL.

    MongoDB vs. MySQL user-friendliness

    MongoDB is an attractive option to developers. Its data storage philosophy is simple and immediately understandable to anybody with programming experience.

    MongoDB stores data in collections with no enforced schema. This flexible approach to storing data makes it particularly suitable for developers who may not be database experts, yet want to use a database to support the development of their applications.

    Compared to MySQL, this flexibility is a significant advantage: to get the best out of a relational database, you must first understand the principles of normalization, referential integrity, and relational database design.

    With the ability to store documents of varying schemas, including unstructured data sets, MongoDB provides a flexible developer interface for teams that are building applications that don’t need all of the safety features offered by relational systems. A common example of such an application is a web application that doesn't depend on structured schemas; it can easily serve unstructured, semi-structured, or structured data, all from the same MongoDB collection.

    MySQL is a common choice for users who have extensive experience using traditional SQL scripting, designing solutions for relational databases, or who are modifying or updating existing applications that already work with a relational system. Relational databases may also be a better choice for applications that require very complex but rigid data structures and database schemas across a large number of tables.

    A common example of such a system could be a banking application that requires very strong referential integrity and transactional guarantees to be enforced to maintain exact point-in-time integrity of data.

    However, it is important to clarify that MongoDB also supports ACID properties of transactions (atomicity, consistency, isolation, and durability). This enables greater flexibility in building a transactional data model that can horizontally scale in a distributed environment and has no impact on performance for multi-document transactions.

    MongoDB vs. MySQL scalability

    A key benefit of the MongoDB design is that the database is extremely easy to scale. Configuring a sharded cluster allows a portion of the database, called a shard, to also be configured as a replica set. In a sharded cluster, data is distributed across many servers. This highly flexible approach allows MongoDB to horizontally scale both read and write performance to cater to applications of any scale.

    A replica set is the replication of a group of MongoDB servers that hold the same data, ensuring high availability and disaster recovery.

    With a MySQL database system, options for scalability are much more limited. Typically, you have two choices: vertical scalability, or adding read replicas. Scaling vertically involves adding more resources to the existing database server, but this has an inherent upper limit.

    स्रोत : www.mongodb.com

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