With these top hand-picked MongoDB interview questions, you will be able to prepare better for your MongoDB interview. As part of these interview questions, you will understand the detailed structure of MongoDB, what its different applications are, how to create a schema in MongoDB, what splitting is, and sharding and aggregation in Mongo database. Learn MongoDB from Intellipaat's MongoDB Course and excel in your career!
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MongoDB is considered to be the best NoSQL database because of its following features:
MongoDB does not use conventional locking with reduction as it is planned to be light, high-speed, and knowable in its presentation. It can be considered as parallel to the MySQL MyISAM auto entrust sculpt. With the simplest business sustain, performance is enhanced, particularly in a structure with numerous servers.
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MongoDB scrap stands on a collection. So, an album of all substances is kept in a lump or mass. Only when there is an additional time slot, there will be more than a few slice data achievement choices, but when there is more than one lump, data gets extended to a lot of slices and it can be extended to 64 MB.
Although MongoDB, Couchbase and Couchbase DB are common in many ways, still they are different in the case of necessities for the execution of the model, crossing points, storage, duplications, etc.
During the sequencing of the names of the database and the collection, the namespace is used.
Yes, it is deleted. Hence, it is better to eliminate the attribute and then save the object again.
Once the functions are done, the old files are converted to backup files and moved to the moveChunk directory at the time of balancing the slices.
When an index is too huge to fit into RAM, then MongoDB reads the index, which is faster than reading RAM because the indexes easily fit into RAM if the server has got RAM for indexes, along with the remaining set.
MongoDB uses the reader–writer locks, allowing simultaneous readers to access any supply like a database or a collection but always offering private access to single writes.
Mongo DB is not considered as a 32-bit system because for running the 32-bit MongoDB, with the server, information and indexes require 2 GB. That is why it is not used in 32-bit devices.
Write operations are saved in memory while journaling is going on. The on-disk journal files are really dependable for the reason that the journal writes are habitual. Inside dbPath, a journal subdirectory is designed by MongoDB.
The snapshot() method is used to isolate the cursors from intervening with writes. This method negotiates the index and makes sure that each query comes to any article only once.
It is a document-oriented database that is used for high availability, easy scalability, and high performance. It supports the dynamic schema design.
It is a group of mongo instances that maintains the same dataset. Replica sets provide redundancy and high availability and are the basis for all production deployments.
There are three main features of MongoDB:
MongoDB provides CRUD operations:
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In MongoDB, sharding means to store data on multiple machines.
In MongoDB, aggregations are operations that process data records and return computed results.
It is the concatenation of the collection name and the name of the database.
We can create a collection in MongoDB using the following syntax:
We can use the following syntax to drop a collection in MongoDB:
Replication is the process of synchronizing data across multiple servers.
In MongoDB, indexes provide high-performance read operations for frequently used queries.
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The following command is used for inserting a document in MongoDB:
GridFS is used for storing and retrieving large files, such as audio, image, and video files.
Journaling is used for safe backups in MongoDB.
We can use the following command to see the connection:
The primary replica set accepts all write operations from clients.
The secondaries replicate the primary replica set’s oplog and apply the operations to their datasets such that the secondaries’ datasets reflect the primary’s dataset.
Profiler is used to show the performance characteristics of every operation against the database.
MongoDB stores data in the form of documents, which are JSON-like field and value pairs.
Replication provides redundancy, and it increases data availability.
Embedded documents capture relationships between data by storing related data in a single document structure.
The application-level encryption provides encryption on a per-field or per-document basis within the application layer.
Storage encryption encrypts all MongoDB data on storage or on the operating system to ensure that only authorized processes can access the protected data.
The createIndex() method is used to create an index.
The oplog records all operations that modify the data in the replica set.
Vertical scaling adds more CPU and storage resources to increase capacity.
Horizontal scaling divides the dataset and distributes data over multiple servers, or shards.
The sharded cluster has the following components:
To create a database, we can use the Database_Name command.
The db.dropDatabse() command is used to drop a database.
The pretty() method is used to show the results in a formatted way.
The remove() method is used to remove a document from a collection.
Projection is used to select only the necessary data. It does not select the whole data of a document.
The limit() method is used to limit the records in the database.
The syntax of the limit() method is as follows:
In MongoDB, the following syntax is used for sorting documents:
The mongodump command is used to create a backup of the database.
In MongoDB, a collection is a group of MongoDB documents.
The db command gives the name of the currently selected database.
The update() and save() methods are used to update documents into a collection.
The syntax of the skip() methopd is as follows:
The mongorestore command is used to restore the backup.
MongoDB uses the dot notation to access the elements of an array and the fields of an embedded document.
Auditing provides administrators with the ability to verify that the implemented security policies are controlling the activity in the system.
The aggregation pipeline is a framework for performing aggregation tasks. The pipeline is used to transform documents into aggregated results.
MapReduce is a generic multi-phase data aggregation modality that is used for processing quantities of data.
Splitting is a background process that is used to keep chunks from growing too large.
C++ is used for writing and implementing MongoDB.
MongoDB uses collections to store data rather than tables.
The save() method is used to replace the existing document with a new document.
MongoDB (from humongous) is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format ‘BSON’), making the integration of data in certain types of applications easier and faster. Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is open-source.
MongoDB was first developed by the software company 10gen (now, MongoDB Inc.) in October 2007 as a component of a planned platform as a service product. Then, the company shifted to an open-source development model in 2009, with 10gen offering commercial support and other services. Since then, MongoDB has been adopted as backend software by a number of major websites and services, including Craigslist, eBay, Foursquare, SourceForge, Viacom, and the New York Times, among others. Currently, MongoDB is the most popular NoSQL database system.
For a better understanding of MongoDB, refer to this What is MongoDB? blog.
MongoDB is a relational database management system (RDBMS) replacement for web applications. So, when we have something close to RDBMS, MongoDB could be of good use.
It gives us the additional partition tolerance, which RDMBS doesn’t offer, but it has problems with availability. Nonetheless, if we want more scalability, MongoDB would be the right choice for us. It’s suitable for real-time analytics and high-speed logging, and it’s highly scalable as well. Craigslist uses MongoDB for archived posts.
Presently, the Internet is loaded with big data, big users, and so on that are becoming more complex day by day. NoSQL is the answer to all these problems; it is not a traditional database management system, not even a relational database management system (RDBMS).
NoSQL stands for ‘Not only SQL’, and it is a type of database that can handle and sort all types of unstructured, messy, and complicated data. It is just a new way to think about databases.
Yes, MongoDB is a NoSQL database.
MongoDB is a document-oriented DBMS.
Although both MongoDB and MySQL are free and open-source databases, there is a lot of difference between them in terms of data representation, relationships, transaction, querying data, schema design and definition, performance speed, normalization, and many more. To compare MySQL with MongoDB is like a comparison between relational and non-relational databases.
MongoDB is a document-oriented DBMS. We can think of it as MySQL but with JSON-like objects comprising the data model, rather than RDBMS tables. Significantly, MongoDB supports neither joins nor transactions. However, it features secondary indexes, an expressive query language, atomic writes on a per-document level, and fully-consistent reads. Operationally, MongoDB offers the master–slave replication with automated failover and built-in horizontal scaling via automated range-based partitioning.
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MongoDB is implemented in C++. However, drivers and client libraries are typically written in their own respective languages. Although, some drivers use C extensions for better performance.
MongoDB uses memory-mapped files. When running a 32-bit build of MongoDB, the total storage size for the server, including data and indexes, is 2 GB. For this reason, we do not deploy MongoDB to production on 32-bit machines.
If we’re running a 64-bit build of MongoDB, there’s virtually no limit to the storage size. For production deployments, 64-bit builds and operating systems are strongly recommended.
While creating a schema in MongoDB, the points need to be taken care of are as follows:
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Nice questions..definitely of great help. Thanks a lot!
Good. It is really useful for us. Thank you very much..
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