Trending October 2023 # Learn Top 8 Nosql Useful Questions And Answers For 2023 # Suggested November 2023 # Top 18 Popular |

Trending October 2023 # Learn Top 8 Nosql Useful Questions And Answers For 2023 # Suggested November 2023 # Top 18 Popular

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Introduction to NoSQL Interview Questions and Answers

NoSQL stands for ‘Not Only SQL.’ NoSQL is designed for larger data sets. These databases are flexible, as they can store and process unstructured and semi-structured data not easily handled by RDBMS, designed primarily for structured data.NoSQL helps in processing big data in real-time web applications. Large-scale organizations, such as Google, Amazon, Facebook, etc., use NoSQL databases to handle massive datasets.

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Below is the top list of 2023 NoSQL Interview Questions and Answers. These questions are divided into two parts as follows:

Part 1 – NoSQL Interview Questions (Basic)

This first part covers basic NoSQL interview questions and answers.

Q1. What do you mean by NoSQL?


NoSQL stands for ‘Not Only SQL,’ but it is also evolved due to some restrictions & challenges with traditional databases. NoSQL databases are designed to manage and work with large distributed data sets effectively. NoSQL databases are highly flexible; they allow us to store and process unstructured and semi-structured data that cannot be easily handled using a relational database system (RDBMS). These databases are used for processing big data in real-time web applications.

Q2. What are the features of NoSQL?


Below are some of the features of NoSQL:

Flexibility: NoSQL offers flexibility to store structured, semi-structured, or unstructured data, unlike a relational database which allows only structured data.

Dynamic Schemas: NoSQL does not require schema definition, which solves the problem of modifying the schema for a table that already contains large datasets and needs new columns added.

Sharding: Sharding means partitioning data into smaller databases to have faster access to data. This feature is present in NoSQL databases, allowing us to quickly fetch data from a server.

Generic: The user can customize the NoSQL database as per the need.

Scaling: NoSQL databases scale horizontally; thus, they are cheaper to manage.

Q3. What is the CAP theorem? How is it applicable to NoSQL systems?


This is the frequently asked NoSQL Interview Questions in an interview. CAP theorem states three basic requirements for an application with distributed architecture.

Consistency: Data in the database must be consistent before and after the execution of any operation. For example, every user should see the same data after an update operation.

Availability: The system should always be up and running; there should be no downtime.

Some examples of CP systems are Big Table, Hyper Table, Mongo DB, and HBase.

Q4. Explain the difference between RDBMS vs NoSQL.



Relational databases are better suited for structured and organized, relational data.

Organize data through normalization.

Use Structured query language(SQL), which is easy to learn.

Maintains Data Integrity

The data and its relationships are stored in separate tables.

ACID compliance ensures that all transactions are committed or none are committed.

Scale-up/ Vertical Scaling.

Better for Unstructured and Unpredictable Data.

Handles Big Data

No predefined schema.

Cheaper to manage.

Scale-out/Horizontal Scaling.

BASE Transaction.

High performance, availability, and scalability.

Part 2 – NoSQL Interview Questions (Advanced) Q5. What are the major challenges with traditional RDBMS?


Following are some of the significant challenges with RDBMS systems:

Not optimized to scale out: RDBMS systems do not optimize horizontal scaling well.

Not able to handle unstructured data: RDBMS systems are not able to handle schema-less data (semi-structured or unstructured)

Costly: There is a high licensing cost for data analysis with RDBMS systems.

Not able to handle the high velocity of data ingestion: RDBMS systems steadily retain data.

The NoSQL systems evolved to overcome all the above challenges.

Q6. What are the different types of NoSQL databases?


There are five different categories of NoSQL databases:

Document Database: The document databases contain many other key-value pairs. A collection contains sets of documents, and each document can contain diverse or heterogeneous fields. A document database also supports nested documents. A user can add custom fields (Dynamic data) to the document.

Consider the below example:

Collection { personName:”Mr. X” person phone:”1234” personAddress:”Andheri” }

Some NoSQL Document databases are Mongo DB, Couch DB, etc.

Some of the NoSQL Column databases are Google’s Big Table, Apache Cassandra, and HBase.

Key-Value stores: It stores the Hashtable of key-value pairs. Hashtable contains a bucket, which is a logical group of keys. In a Hashtable, a key can be auto-generated or synthetic, while the value can be a String, JSON, or BLOB. Consider the below example where a key is a city and value is an address in that city.

Key Value

“Mumbai” {“Andheri, Mumbai, Maharashtra, India”}

“Bhopal” {“New Market, Bhopal, Madhya Pradesh, India”}

“Pune” {“Hadapsar, Pune, Maharashtra, India”}

Redis, CouchBase Server, Amazon’s Dynamo.

Example: Redis and Memcache

One of the NoSQL Graph databases is Neo4J.

Q7. How does NoSQL relate to big data?


NoSQL databases are specifically designed to meet the requirements of handling large volumes of data, commonly referred to as “Big Data.” Since a fixed schema model does not bind them, this makes them suitable for today’s business needs where there is a large volume of non-uniform data (Big Data).

Q8. Can you explain the transaction support by using a BASE in NoSQL?


The CAP theorem states that distributed systems cannot achieve all three properties simultaneously: consistency, availability, and partition tolerance. The BASE system gives up on consistency while maintaining the other two. The BASE system works well despite physical network partitions and always allows a client with reading and write availability.

The BASE stands for:

Eventual consistency

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