Top 25 MongoDB Interview Questions and Answers in 2022


MongoDB Interview Questions and Answers

MongoDB is one of the most common open-source NoSQL databases, and it is written in the C++ language and uses JSON-like documents with optional schemas. You will mainly be asked about this open-source database in your upcoming data computing or programming interview, and to help you pass, we will look at some of the common questions to expect.

Take a look at the following questions and brainstorm the best answers to give the interviewer and stand a better chance of getting your data computing or programming job.

1. Define MongoDB

MongoDB is an open-source database that uses JSON-like documents complete with optional schemas. It is written in C++ language and offers more effortless scalability. This cross-platform and document-oriented database functions on the concept of collection and documentation. It has various valuable features, such as range queries, secondary indices, aggregations, sorting and geospatial indexes.

2. Can You Mention The Advantages Of MongoDB?

This database comes with several advantages, given that it is open-source. It offers primary and secondary support in fields and uses a dynamic database schema. MongoDB also allows easier scalability and comes with built-in data partition support. This open-source database further uses JavaScript objects instead of procedures, which comes with its fair share of advantages.

3. Mention All The Features Of MongoDB

MongoDB has several features, which explains its versatility. These include sharding which is the process of data splitting across different machines; file storage, thanks to its convenient protocol that stores large files and metadata; and aggregation, thanks to its aggregation framework based on data processing pipelines and special collection and index types. These special collections and index types include time-to-live data collections with a given time limit.

Why Should We Hire You? 5 Best Answ...
Why Should We Hire You? 5 Best Answers

4. When Is It Advisable To Use MongoDB?

MongoDB comes in handy when building business and internet applications that evolve fast and scale efficiently. It best works for those building scalable solutions via agile methodologies. Some of its use cases include rapid iterative development support, massive Cali g of data repository, the evolution of deployment type when the business changes, storage, management and searching if data via different dimensions, and data scaling to high read and write traffics. These reasons explain why this open-source platform is advisable for different developers.

5. Can You Explain What Geospatial Indexes Are In MongoDB?

MongoDB comes with two types of geospatial indexes, namely 2dsphere and 2d. 2dsphere indexes. These normally work in unison with spherical geometries that use the WGS84datum that model the Earth’s surface as an oblate spheroid. Due to this type of modeling, there is always a flattening at the poles. We consider the Earth’s scope when calculating distance via the 2sphere indexes. The result obtained is a better and more accurate treatment of distance. For points stored on a two-dimensional plane, 2d indexes are used. 2dsphere comes in handy when specifying geometries for different lines, points and polygons, provided that the format is JSON. A two-element array then grants the point and is normally represented by a two-element collection.

6. Explain What Transactions Are In MongoDB

In MongoDB, transactions refer to logical processing units in databases with one or more database operations. These can either be read or write operations. The essence of these units is to offer consistency in MongoDB. As a result, this open-source platform has two APIs: core and call-back API. The core API has the same syntax as relational databases, while call-back APIs are the most used approach for transactions. It is capable of starting a transaction, executing given operations, and committing.

7. Tell Us More About Mongo DB’s Aggregation Framework

MongoDB has an aggregation framework- a collection of tools used for analysis within the MongoDB framework. Thanks to these tools, one can easily analyze documents in several groups. This aggregation framework’s operation is based on a pipeline concept, meaning input is taken from a given MongoDB collection. The document from the collection is passed through several stages, each performing different operations on the inputs. Therefore, every new step considers the former stage’s output as its input, even though all of them are documents.

8. What Are Some Of The Things One Should Do When Creating Schema In MongoDB?

Several points should be considered when creating a schema in MongoDB. These ensure that the schema creation is successful. They include designing the schema according to the different user requirements, doing joins while writing and not when a read operation is going on, doing complex aggregation on the schema, frequenting use cases for schema optimization, and combining objects into a given document. However, depending on the preferred working style, one can also choose to separate these documents.

9. Can You Differentiate Between MongoDB And Cassandra?

Cassandra, fully known as Apache Cassandra, is an open-source NoSQL Database used by several companies owing to its high scalability and availability. It is quite different from MongoDB since it is a high-performance distributed database system, while the latter is a cross-platform and data-oriented database system. MongoDB is also developed in C++, while Cassandra runs in Java. Lastly, Cassandra offers high availability, which explains why most enterprises love it. On the other hand, MongoDB is lauded for being simple to administer database in case of failure. All in all, they are still some of the most renowned databases.

10. What Do You Think People Should Look Out For In A Database?

One should use the right criteria when choosing a database for their application. A good database should be cost-friendly and easy to maintain. You should be able to access all the necessary features at a particular cost instead of paying extra for additional features. It is also imperative that one looks out for service stability and database performance. Other factors to consider are scalability and security, which are some of the reasons organizations prefer some databases to others.

11. Mention All The Use Cases Of MongoDB

MongoDB is mostly used to store data for operational requirements in different organizations. It can handle 4/5 of today’s applications, given that it is simple to use and offer better features and services than relational databases. It is also pretty outstanding in its use cases and comes in handy to remedy relational database faults, such as when handling structured and semi-structured data. This database also comes in handy when handling applications that require challenging transactions. Scan-based applications that can access huge data subsets are furthermore properly handled by this database. Lastly, the MongoDB database has general uses such as mobile applications, product catalogs, real-time personalization, and content management.

12. Mention Some Instances That Call For Data Normalization In MongoDB

Data Normalization in MongoDB is highly dependent on objectives. Normalization ensures that the database achieves the representation of useful data. Denormalization reverses the effect by making the reading of such data effective. Embedded data models are, therefore, normally used when there are ‘contains’ relationships between different entities and where there exist several relationships among entities too. To answer the question, normalized data models are often used to represent challenging many-to-many relationships, model big hierarchical data sets, and for the embedding of results in data duplication.

13. Contrast Mongodb With CouchDB

Apache CouchDB is a unique storage system that, like MongoDB, comes with advantages. This open-source and document-oriented NoSQL Database serves the same function as MongoDB. It has several differences from MongoDB. However, the main ones lie in the speed, availability of triggers, and serialization. MongoDB is generally quicker than Couch DB. It doesn’t have triggers as opposed to the latter and serializes JSON data to Bison while CouchDB does not. However, on the bright side, CouchDB is generally more secure than MongoDB.

14. Mention The Fields In Capped Collection Syntax

There are five fields in capped collection syntaxes that serve different functions. The most common is the collection name field, which the collection name generally creates as the limited collection; the capped field is a Boolean field that by default has a false value, and the auto indexes field, which is a Boolean flag used for auto-indexing purposes. The size field represents the maximum number of documents in bytes and comes in handy in capped collections. In contrast, the max field represents the highest quantity of documents that allow a given collection.

15. I Want To Start The MongoDB Instance On Server. What Should I Do?

Starting the MongoDB Instance or Server is quite simple, provided all the right steps are followed. This is done by first opening the command prompt and executing the MongoDB.exe file while retreating to the path where the MongoDB database was installed. Next, head to the bin folder and locate the “mongod.exe” file, then double-click it for execution purposes. Lastly, proceed to the respective folder and type ‘mongo,’ which should connect MongoDB through the shell.

16. What Is The Difference Between Mongodb And RDBMS?

MongoDB and RDMBS can be compared based on their work, scalability, performance, join support, query language, JavaScript support, and hierarchical data storage. In their definition, MongoDB is a non-relational database, while RDMBS is a relational database management system. The former works over relationships among the tables using columns and rows, while the latter is a document-oriented database system that uses fields and documents. As for scalability, MongoDB is horizontally and vertically scalable, while RDMBS is only vertically scalable. When it comes to performance, MongoDB enhances its performance as the processors rise, while for RDMBS, performance is enhanced with the rise in RAM capacity. MongoDB does not also support difficulty joins, while RDMBs support complex binds. Lastly, MongoDB uses BSON for database querying, while RDBMS uses SQL.

17. Can You Mention The Different Kinds Of Indexes In MongoDB

There are six types of indexes in this database. We have compound, multi-key, single field, geospatial, and hashed indexes. The compound index comes in handy in multiple areas, while multi-key indexes help arrange data. Single field indexes sort and indexes over a given field, while their geospatial counterparts come in handy in querying the location data. We also have hashed indexes that index hashes on several fields. These indexes play a great role in MongoDB, as seen from the illustrations.

18. Define What NoSQL Databases Are And Tell Us Whether Mongodb Falls Under The Same Category

NoSQL is the short form for Not Only SQL. It is a database-type capable of handling and sorting different unstructured, complicated, or even semi-structured data. This is a great improvement to the existing database systems, which were quite demanding, especially with the data they handled. NoSQL databases, therefore, come in handy for large and complex data types. MongoDB is a NoSQL database given that it can handle all data types, including the most complex.

19. What Are The Disadvantages Of NoSQL Databases?

NoSQL databases also have disadvantages despite their widespread usage. They face a lack of standardization given that despite their increasing numbers, they don’t have a standard like the one in relational databases. Some do not also offer cross-platform support and do not, therefore, run on non-Linux operating systems. Developers also undergo compatibility issues with SQL instructions, which is a huge disadvantage. Lastly, poor usability is also a crippling issue since these databases lack good management tools.

20. Can You Mention The Advantages And Disadvantages Of Normalizing Data In The MongoDB Database?

Normalized data ensures the faster update of documents, unlike denormalized data, which is generally slow. The same applies to other relational database management systems, not just the NoSQL databases. On the bright side, denormalized data can be read faster, which is a big advantage. However, it comes with its fair share of disadvantages, the main one being the inability to synchronize such data as it generally takes up more space. MongoDB is a NoSQL database, meaning that it does not support data normalization but instead requires the client applications to handle this role. However, one can run audits, ensuring that the app data is similar to the expected patterns by MongoDB.

21. Can You Mention The Differences Between BSON Documents In Mongodb And The General JSON Documents?

JSON, which stands for JavaScript Object Notation, is a human-readable document format that comes in handy in data exchange. It is the most popular data exchange standard on the web, given that it supports several data styles such as numbers, strings, Booleans, and arrays.

On the other hand, BSON is a binary encoding used to store documents. Even though it is similar to JSON in one way or another, it allows the latter to support other data types such as ‘Date.’ BSON Documents are also ordered, meaning they occupy less space. Also, BSON can be encoded and decoded easily, given that it is binary.

22. When Should Someone Use A NoSQL Database?

 There are several factors and scenarios that necessitate the use of a NoSQL database. These databases come in handy in fast-paced agile development, given their edge over relational databases. They are used for the storage or computation of structured and semi-structured data as well as in the handling of large data volumes. We also need NoSQL databases in modern applications such as real-time streaming and microservices. Lastly, they come in handy when out-of-scale architecture is required.

23. What Are Some Of The Normal Misconceptions About A NoSQL Database, Such As MongoDB?

One of the most common misconceptions about NoSQL databases is that they do not support ACID transactions when some examples, such as MongoDB, actually support such transactions. This is because these databases can easily eliminate the need to multi-record transactions during different uses. Some people also believe that relational databases handle relationship data best when in the real sense, NoSQL databases can also handle such data because they have different storage types and means. It is even easier to model such data in NoSQL databases as compared to relational databases.

24. Can You Mention The Features And Types Of NoSQL Databases Such As MongoDB?

NoSQL databases have similar features, even though they are unique. Most of the databases in this category I have interacted with have horizontal scaling, flexible schemas, and fast queries given their type of data model. They are also easier to use, explaining why most developers love them. As for the types of NoSQL databases, we have wide-column stores, graph databases, key-value databases, and document databases. Every item has keys and values in key-value databases, while data is stored on nodes and edges for graph databases. In document databases, information is stored in documents resembling JSON objects. Such documents have values and fields.

25. How Confident Are You When It Comes To Suing This Database?

I am confident in my ability to use MongoDB for different processes that this organization holds dear. I would like to point out that I have used MongoDB for five years now for data computation purposes in separate entities.

Conclusion

We have covered some of the most common MongoDB questions you can expect in your upcoming interview. Ensure that you are well-versed in this database before your interview to land the job you are currently interviewing for. We wish you all the best in your upcoming interview.

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