MongoDB has established itself as one of the leading NoSQL databases and is widely utilized across industries. Gaining expertise in MongoDB can be immensely beneficial for working with modern database technology and applications that rely heavily on data-driven insights.
MongoDB, which emerged in 2007, is an open-source document database with a scalable, horizontally-oriented architecture and employs a flexible schema for data storage. With a robust global developer community, MongoDB separates itself from the traditional approach of storing data in rows and columns within SQL databases.
Preparing for MongoDB interviews is a great way to demonstrate your understanding of the database system, its features, and best practices. MongoDB interview questions typically include technical and scenario-based queries that assess your proficiency in working with the database system.
Being well-prepared can enable you to confidently answer MongoDB interview questions about data modeling, querying, performance optimization, replication, and other MongoDB-related topics. This knowledge can set you apart from other candidates and enhance your chances of landing the job.
Answer: MongoDB means a cross-platform, document-oriented database. It is a NoSQL database that disregards the traditional table-based relational database structure for JSON-like documents having dynamic schemas. Thus, MongoDB makes data integration faster and easier in some applications. It was released under a combination of Apache License and GNU Affero General Public License. MongoDB was adopted as backend software by several leading websites and services, including eBay, Viacom, Craigslist, Foursquare, SourceForge, the New York Times, etc. Currently, MongoDB is the most popular open-source NoSQL database system.
Answer: MongoDB stores Binary Interchange and Structure Object Notation (BSON) objects in a collection. The concatenation of a database name and collection name is known as the namespace.
Answer: Sharding refers to the process of storing data records amongst multiple machines applied by MongoDB to meet the data growth demands. It builds a horizontal partition in a database where each partition is known as the database shard or a shard.
Answer: A replica set in MongoDB is a group of Mongo instances that host the same data set. In the replica set, a node is primary while another node is secondary. Data replicated from the primary to the secondary node.
Answer: MongoDB achieves replication by using the replica set. In a replica, the primary node receives all write operations. Other instances, like secondaries, apply operations from primary so that they have the same data set. A replica set can have a single primary node.
- It is a group of two or more nodes (at least three nodes are needed).
- In the replica set, one node is the primary node, while the remaining ones are secondary.
- All data replicates from the primary node to the secondary node.
- During automatic failover or maintenance, elections are established for primary, and a new primary node gets elected.
- After recovering of a failed node, it again joins the replica set and now works as the secondary node.
Answer: When creating a schema in MongoDB, taken care of these points:
- Design the schema according to the user’s requirement.
- If we want to use different objects together, combine them into one document; otherwise, separate them.
- Do joins when on write, and not when it is on read.
- For most common use cases, optimize your schema.
- Do complex aggregation in your schema.
Answer: MongoDB has a database profiler that shows performance characteristics of all the operations against a database. Using the profiler, you can find queries and write operations (slower than they should be) and use that information to determine when an index is required.
Answer: Yes, one can move old files into the moveChunk directory during the normal shard balancing operations. These old files are made as backups that can be deleted once the operations are complete.
Answer: Indexes in MongoDB are known as special structures that store a small part of a dataset in an easy-to-traverse form. Indexes help to execute queries efficiently. Without indexes, MongoDB should perform a collection scan (scan each document in a collection) to select those documents that match the query statement. MongoDB can use an index to limit the no. of documents it must inspect if an appropriate index exists for the query.
Answer: GridFS is a specification in MongoDB for storing and retrieving large files such as audio files, images, video files, etc. It is a file system that only stores files, but its data is stored in the MongoDB collections. GridFS can store large files even bigger than its document size limit (16MB). It divides a file into chunks and stores every chunk of data in a separate document, each having a maximum size of 255k.
Answer: Below are some good alternatives to MongoDB:
- RethinkDB: It is an open-source, scalable DBMS system that simplifies real-time app development. This alternative of MongoDB provides API monitoring, flexible query language, interactive operations, and it is easy to learn and install. The following are some salient features of RethinkDB:
- It helps you build saleable real-time applications with ease.
- You can develop modern applications using any web framework.
- It helps you pair with real-time technologies such as Socket.io and SignalR.
- It enables you to integrate the latest advances in technology.
- OrientDB- It is another open-source NoSQL multi-model database. It helps to optimize security and performance while supporting scalability. Features:
- It is focused on high performance and scalability.
- The unified multi-model API for quicker deployment
- TinkerPop3 for effective and fast upgrades
- Enhanced query planner & the executor
- CouchDB- It is built to provide web accessibility that supports an array of devices. Here, data is stored in the JSON format and organized into the key-value pairs similar to the MapReduce format. Features:
- It allows you to run one logical database server that can be run on different virtual machines.
- CouchDB tool also renders interaction with an external tool like load balancers, HTTP proxy servers, etc.
- Session Support and authentication ensures durability and security
- The multi-node cluster enables you to save data redundantly and efficiently.
- ArangoDB- It is another multi-model Database Management System that is widely used like MongoDB. It supports three kinds of data models with a database core and a query language, AQL. Features:
- ArrangoDB is designed to create a multi-node database model which supports document, graphs, value or key pairs.
- It operates as a highly scalable database cluster for all the data models.
- It can run in a data center, and the data can be replicated to another data center without disturbing data authenticity.
- High-security features are installed to safeguard data.
- PostgreSQL- It is a widely used and popular open-source DBMS. PostgreSQL provides support for SQL for relational and JSON for non-relational queries. Thus, it efficiently performs with both structured & unstructured data. Features:
- It offers support for multi-version concurrency control
- PostgreSQL efficiently uses the client-server network architecture
- It offers high availability and a standby server to maintain the flow
- It is compatible with the object-oriented model and ANSI-SQL2008.
- Cassandra- It is an ideal tool when users need both scalability and high availability and not affecting performance. Apache Cassandra offers support data replication across multiple data centers. Thus, it provides durability and security without compromising on efficiency. Features:
- Data is replicated to various nodes to provide a fault-tolerance system and ensures durability.
- The network bottlenecks are reduced as each node in a cluster is separate and can function independently.
- Support for services and contracts from third parties can be made possible through Cassandra.
- It helps you choose between synchronous or asynchronous data replication for every update.
Answer: Presently, the internet is bombarded with Big Data complexity, and data is becoming more complex day by day. NoSQL provides answers to all such problems; it is not the traditional DBMS, not even an (RDBMS) relational database management system. Not Only SQL, abbreviated as NoSQL, is a database type that can sort and handle all types of complicated and unstructured data. Yes, MongoDB is a NoSQL database.
Answer: MongoDB provides official driver support for C++, Java, C#, C, PHP, Node.js, Perl, Python, Scala, Ruby, Erlang, and Go. You can utilize MongoDB with any of these languages.
Answer: NoSQL database can be classified into the following types:
- Key-value store NoSQL database
- Document store NoSQL database
- Column store NoSQL database
- Graph base NoSQL database
Answer: MongoDB and SQL databases are two polar opposite sides of a backend world. MongoDB deals with chaotic, unstructured data, whereas SQL databases work with organized, structured data. Both have their own set of pros and cons, but they are meant for different use cases. MongoDB doesn’t have any restrictions on schema design.
Answer: Below are key differences between MySQL and MongoDB:[fusion_table fusion_table_type=”1″ fusion_table_rows=”” fusion_table_columns=”” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” class=”” id=”” animation_type=”” animation_direction=”left” animation_speed=”0.3″ animation_offset=””]
[/fusion_table]
| MongoDB | MySQL |
|---|---|
| MongoDB displays data as JSON documents. | MySQL displays data in rows and tables. |
| In MongoDB, you don’t have to define a schema. Rather you can drop in documents and don’t even need to have the same fields. | MySQL requires you to define columns and tables before storing anything, and each row in the table must have equal columns. |
| MongoDB stands on a pre-defined structure that can be defined and adhered to; also, it can have different structures if you require different documents in the collection. | MySQL uses (SQL) Structured Query Language for database access. You can’t change the schema. |
| MongoDB supported two programming languages C & C++ | MySQL support three languages C, C++ and JavaScript |
| Ongoing development is done through MongoDB, Inc. | Constant development is done through the Oracle Corporation. |
| MongoDB supports sharding, built-in replication, and auto-elections. | MySQL supports master replication and master-slave replication. |
| If an index is not found, each document within the collection must be scanned to select documents that offer a match to a query statement. | If an index is not defined, a database engine will scan the entire table to find all relevant rows. |
| MongoDB is best suited for most cloud-based services. | MySQL is the best option if your priority is data security. |
| MongoDB doesn’t place any restrictions on the schema design. | MySQL requires you to define your columns and tables before you can store anything. Every row in the table must have the same columns. |
| MongoDB utilizes JavaScript as query language. | MySQL uses (SQL) Structured Query Language. |
| MongoDB doesn’t support JOIN operations. | MySQL supports JOIN operations. |
| It can handle large unstructured data. | MySQL is slow as compared to MongoDB when dealing with large databases. |
| No schema definition, so it has a lesser risk of attack because of design. | Risk of SQL injection attacks |
| An ideal choice when you have structured or unstructured data with the potential for rapid growth. | An ideal choice if you have structured data and need a traditional relational database. |
Answer: Mongo DB is the best NoSQL database because of its features such as:
- Document-Oriented
- High Performance
- Rich Query language
- Highly Available
- Easily Scalable
Answer: Yes, we can achieve the primary key and foreign key relationship by embedding a document inside another, such as embed an address document inside the customer document.
Answer: ObjectID in MongoDB has a 12-byte BSON type described as follows:
- 4 bytes value representing seconds
- 3 bytes machine identifier
- 2 bytes process id
- 3 bytes counter
Answer: MongoDB is implemented and written in C++ language. However, client libraries and drivers are typically written in their respective programming languages. Some drivers also the use C language for better performance.