TOP 50 MongoDB Interview Questions

MongoDB Interview Questions

1) What do you understand by NoSQL databases? Is MongoDB a NoSQL database? explain.

NoSQL databases are a type of database that does not use the traditional SQL (Structured Query Language) for storing and retrieving data. They are designed to handle large amounts of data that may not fit neatly into a table structure, and are often used for modern web applications that require flexible, scalable data storage.

MongoDB is a NoSQL database that is based on the document-oriented model. In this model, data is stored as documents in a collection, rather than in tables with rows and columns like a traditional relational database. Each document can have a different structure, making it easy to store and retrieve complex data structures. MongoDB is known for its high performance, scalability, and flexibility, and is often used for modern web applications and other applications that require fast access to large amounts of data.

Yes. MongoDB is a NoSQL database.

2) Which are the different languages supported by MongoDB?

MongoDB supports a wide range of programming languages, including:

In addition to these languages, MongoDB also provides drivers for other languages, such as PHP, Swift, and Kotlin.

3) What are the different types of NoSQL databases? Give some example.

NoSQL database can be classified as 4 basic types:

1. Key value store NoSQL database
2. Document store NoSQL database
3. Column store NoSQL database
4. Graph base NoSQL databse

There are many NoSQL databases. MongoDB, Cassandra, CouchBD, Hypertable, Redis, Riak, Neo4j, HBASE, Couchbase, MemcacheDB, Voldemort, RevenDB etc. are the examples of NoSQL databases.

4) Is MongoDB better than other SQL databases? If yes then how?

MongoDB is better than other SQL databases because it allows a highly flexible and scalable document structure.

For example:

• One data document in MongoDB can have five columns and the other one in the same collection can have ten columns.
• MongoDB database are faster than SQL databases due to efficient indexing and storage techniques.

5) What type of DBMS is MongoDB?

MongoDB is a type of NoSQL database, specifically a document-oriented database. It is designed to handle large amounts of data that may not fit neatly into a table structure, and is often used for modern web applications that require flexible, scalable data storage.

In a document-oriented database like MongoDB, data is stored as documents in a collection, rather than in tables with rows and columns like a traditional relational database. Each document can have a different structure, making it easy to store and retrieve complex data structures. MongoDB uses JavaScript as its primary programming language and is known for its high performance, scalability, and flexibility.

6) What is the difference between MongoDB and MySQL?

MongoDB and MySQL are both popular database management systems, but they have some significant differences:

In summary, MongoDB is a NoSQL database that is designed for flexible, scalable data storage, while MySQL is a traditional relational database that is designed for structured data storage and efficient querying using SQL. Both databases have their own strengths and are well-suited for different use cases.

7) Why MongoDB is known as best NoSQL database?

MongoDB is often considered to be the best NoSQL database for a number of reasons:

1. Flexibility: MongoDB stores data as JSON-like documents, which means that each document can have a different structure. This makes it easy to store and retrieve complex data structures, and allows for a high degree of flexibility in the data model.
2. Scalability: MongoDB is designed to handle large amounts of data, and is highly scalable. It can be easily deployed on a distributed system with multiple servers, allowing it to handle the largest data loads and highest throughput.
3. Performance: MongoDB is known for its high performance, especially for read operations. It uses a memory-mapped file system, which allows it to access data directly from memory, resulting in faster performance.
4. Ease of use: MongoDB has a simple, easy-to-use API and a user-friendly shell, making it easy for developers to work with.
5. Wide adoption: MongoDB has a large and active user community, and is used by many well-known companies. This means that it has a lot of support and resources available, and is constantly being improved and updated.

Overall, MongoDB’s flexibility, scalability, performance, ease of use, and wide adoption make it a popular choice for many modern web applications and other data-intensive applications.

8) Does MongoDB support primary-key, foreign-key relationship?

In MongoDB, relationships between data are usually modeled using references (also known as “foreign keys”). A reference is a field in a document that contains the unique identifier of another document. To model a one-to-many relationship between two collections, for example, you might create a “posts” collection and a “comments” collection, and then add a “post_id” field to the “comments” collection that references the “_id” field of the corresponding post.

MongoDB does not enforce referential integrity, which means that there is no automatic mechanism to ensure that a referenced document actually exists in the database. It is up to the application to ensure that references are valid.

MongoDB does not support primary keys in the traditional sense. Each document in a collection has a unique identifier called the “_id” field, which is generated automatically by the database if not specified by the application. However, the “_id” field is not required to be unique across collections, and it is not used to enforce relationships between collections. Instead, relationships are usually modeled using references as described above.

9) Can you achieve primary key – foreign key relationships in MongoDB?

We can achieve primary key-foreign key relationship by embedding one document inside another. For example: An address document can be embedded inside customer document.

MongoDB Interview Questions

10) Does MongoDB need a lot of RAM?

No. There is no need a lot of RAM to run MongoDB. It can be run even on a small amount of RAM because it dynamically allocates and de-allocates RAM according to the requirement of the processes.

11) Explain the structure of ObjectID in MongoDB.

ObjectID is a 12-byte BSON type. These are:

• 4 bytes value representing seconds
• 3 byte machine identifier
• 2 byte process id
• 3 byte counter

12) Is it true that MongoDB uses BSON to represent document structure?

Yes.

13) What are Indexes in MongoDB?

In MondoDB, Indexes are used to execute query efficiently. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement. If an appropriate index exists for a query, MongoDB can use the index to limit the number of documents it must inspect.

14) By default, which index is created by MongoDB for every collection?

By default, the_id collection is created for every collection by MongoDB.

15) What is a Namespace in MongoDB?

Namespace is a concatenation of the database name and the collection name. Collection, in which MongoDB stores BSON objects.

16) Can journaling features be used to perform safe hot backups?

Yes.

17) Why does Profiler use in MongoDB?

MongoDB uses a database profiler to perform characteristics of each operation against the database. You can use a profiler to find queries and write operations

18) If you remove an object attribute, is it deleted from the database?

Yes, it be. Remove the attribute and then re-save() the object.

19) In which language MongoDB is written?

MongoDB is written and implemented in C++.

20) Does MongoDB need a lot space of Random Access Memory (RAM)?

No. MongoDB can be run on small free space of RAM.

21) What language you can use with MongoDB?

MongoDB client drivers supports all the popular programming languages so there is no issue of language, you can use any language that you want.

22) Does MongoDB database have tables for storing records?

No. Instead of tables, MongoDB uses “Collections” to store data.

23) Do the MongoDB databases have schema?

Yes. MongoDB databases have dynamic schema. There is no need to define the structure to create collections.

24) What is the method to configure the cache size in MongoDB?

MongoDB’s cache is not configurable. Actually MongoDb uses all the free spaces on the system automatically by way of memory mapped files.

25) How to do Transaction/locking in MongoDB?

MongoDB doesn’t use traditional locking or complex transaction with Rollback. MongoDB is designed to be light weighted, fast and predictable to its performance. It keeps transaction support simple to enhance performance.

26) Why 32 bit version of MongoDB are not preferred ?

Because MongoDB uses memory mapped files so when you run a 32-bit build of MongoDB, the total storage size of server is 2 GB. But when you run a 64-bit build of MongoDB, this provides virtually unlimited storage size. So 64-bit is preferred over 32-bit.

27) Is it possible to remove old files in the moveChunk directory?

Yes, These files can be deleted once the operations are done because these files are made as backups during normal shard balancing operation. This is a manual cleanup process and necessary to free up space.

28) What will have to do if a shard is down or slow and you do a query?

If a shard is down and you even do query then your query will be returned with an error unless you set a partial query option. But if a shard is slow them Mongos will wait for them till response.

29)Explain the covered query in MongoDB.

A query is called covered query if satisfies the following two conditions:

• The fields used in the query are part of an index used in the query.
• The fields returned in the results are in the same index.

30) What is the importance of covered query?

Covered query makes the execution of the query faster because indexes are stored in RAM or sequentially located on disk. It makes the execution of the query faster.

Covered query makes the fields are covered in the index itself, MongoDB can match the query condition as well as return the result fields using the same index without looking inside the documents.

31) What is sharding in MongoDB?

In MongoDB, Sharding is a procedure of storing data records across multiple machines. It is a MongoDB approach to meet the demands of data growth. It creates horizontal partition of data in a database or search engine. Each partition is referred as shard or database shard.

32) What is replica set in MongoDB?

A replica can be specified as a group of mongo instances that host the same data set. In a replica set, one node is primary, and another is secondary. All data is replicated from primary to secondary nodes.

33) What is primary and secondary replica set in MongoDB?

In MongoDB, primary nodes are the node that can accept write. These are also known as master nodes. The replication in MongoDB is single master so, only one node can accept write operations at a time.

Secondary nodes are known as slave nodes. These are read only nodes that replicate from the primary.

34) By default, which replica sets are used to write data?

By default, MongoDB writes data only to the primary replica set.

35) What is CRUD in MongoDB?

MongoDB supports following CRUD operations:

• Create
• Read
• Update
• Delete

36) In which format MongoDB represents document structure?

MongoDB uses BSON to represent document structures.

37) What will happen when you remove a document from database in MongoDB? Does MongoDB remove it from disk?

When you remove a document from a MongoDB collection, the database will mark the space occupied by the document as available for reuse. However, the actual data is not immediately removed from the disk.

MongoDB uses a technique called “data file preallocation” to improve performance by minimizing the amount of disk I/O needed to write data to the database. When data is inserted or updated, MongoDB will allocate a certain amount of space on the disk in advance, and the data is written to this preallocated space. When a document is deleted, the space it occupied is marked as available for reuse, but the data is not actually removed from the disk.

Instead, the data is marked as “unused” and will be overwritten when new data is written to the database. This means that when a document is deleted, it is not immediately removed from the disk, but the space it occupied will eventually be overwritten with new data.

To completely remove deleted data from the disk, you can use the “compact” command in the MongoDB shell, which will defragment the data files and reclaim any unused space. This process can be resource-intensive, and is usually not necessary unless you need to free up disk space or optimize the database for performance.

38) Why are MongoDB data files large in size?

MongoDB data files can be large in size for a number of reasons:

1. Data file preallocation: As mentioned in a previous answer, MongoDB uses a technique called “data file preallocation” to improve performance by minimizing the amount of disk I/O needed to write data to the database. When data is inserted or updated, MongoDB will allocate a certain amount of space on the disk in advance, and the data is written to this preallocated space. This can result in data files that are larger than the actual amount of data being stored.
2. Large documents: MongoDB is designed to store large amounts of data, and it is common for documents in a MongoDB collection to be relatively large. This can contribute to the size of the data files.
3. Indexes: Indexes in MongoDB are stored as part of the data files, and they can take up a significant amount of space. If you have many indexes or large indexes, this can contribute to the size of the data files.
4. Unused space: As mentioned in a previous answer, when a document is deleted from a MongoDB collection, the space it occupied is marked as available for reuse, but the data is not immediately removed from the disk. This can result in large gaps of unused space within the data files.

Overall, the size of the data files in a MongoDB database will depend on the amount and size of the data being stored, as well as the number and size of the indexes. Compact the data files to reclaim unused space.

39) What is a storage engine in MongoDB?

A storage engine is the part of a database that is used to manage how data is stored on disk.

For example: one storage engine might offer better performance for read-heavy workloads, and another might support a higher-throughput for write operations.

40) Which are the storage engines used by MongoDB?

MMAPv1 and WiredTiger are two storage engine used by MongoDB.

41) What is the usage of profiler in MongoDB?

A database profiler is used to collect data about MongoDB write operations, cursors, database commands on a running mongod instance. You can enable profiling on a per-database or per-instance basis.

The database profiler writes all the data it collects to the system. profile collection, which is a capped collection.

42) Is it possible to configure the cache size for MMAPv1 in MongoDB?

No. it is not possible to configure the cache size for MMAPv1 because MMAPv1 does not allow configuring the cache size.

43) How to configure the cache size for WiredTiger in MongoDB?

For the WiredTiger storage engine, you can specify the maximum size of the cache that WiredTiger will use for all data. This can be done using storage.wiredTiger.engineConfig.cacheSizeGB option.

44) How does MongoDB provide concurrency?

MongoDB uses reader-writer locks for concurrency. Reader-writer locks allow concurrent readers shared access to a resource, such as a database or collection, but give exclusive access to a single write operation.

45) What is the difference between MongoDB and Redis database?

Difference between MongoDB and Redis:

• Redis is faster than MongoDB.
• Redis has a key-value storage whereas MongoDB has a document type storage.
• Redis is hard to code but MongoDB is easy.

46) What is the difference between MongoDB and CouchDB?

Difference between MongoDB and CouchDB:

• MongoDB is faster than CouchDB while CouchDB is safer than MongoDB.
• Triggers are not available in MongoDB while triggers are available in CouchDB.
• MongoDB serializes JSON data to BSON while CouchDB doesn’t store data in JSON format.

47) What is the difference between MongoDB and Cassandra?

Difference between MongoDB and Cassandra:

• MongoDB is cross-platform document-oriented database system while Cassandra is high performance distributed database system.
• MongoDB is written in C++ while Cassandra is written in Java.
• MongoDB is easy to administer in the case of failure while Cassandra provides high availability with no single point of failure.

48) Is there any need to create database command in MongoDB?

You don’t need to create a database manually in MongoDB because it creates automaically when you save the value into the defined collection at first time.

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