Carl Strozz coined the concept of NoSQL in 1998. NoSQL refers to a non-SQL or non-relational Data Management System which provides a mechanism for retrieving and storing data. The main reason behind the popularity of NoSQL is its capability to store and handle structured, semi-structured, unstructured, and polymorphic data. NoSQL is hugely popular in Big data and real-time web apps, which is increasing firmly. For example, companies like Google, Twitter, and Facebook collect terabytes of user data daily. Let’s take a look at some of the interview questions on NoSQL.
The learning objectives of this blog include the following:
1. A common understanding of NoSQL, its features, and how it is better than relational databases.
2. Knowledge of CAP theorem, scalability, and normalization in NoSQL.
3. Understanding Big SQL, Impala, and Polyglot persistence in NoSQL.
This article was published as a part of the Data Science Blogathon.
Answer: Key-value
Explanation: It is considered the simplest NoSQL database as it stores all items as an attribute name (i.e., “key”) and its corresponding value that is easy to fetch.
Answer: SAN
Explanation: In order to make hardware act as a single server we can easily achieve SAN and other complex arrangements.
Answer: Cassandra
Explanation: Databases like Cassandra and HBase are efficient to deal with queries over huge volumes of data and store that in the form of columns instead of rows.
Answer: Sharding
Explanation: Sharding is a popular process where a shard key is used to split the data into ranges and distribute it across various shards.
Answer: AMS
Explanation: AMS can help by load balancing features and facilitates data replication.
Answer: Document Databases
Explanation: In Document databases, the data is stored as a key value where every key pairs with a complex data structure(document).
Answer: Backend
Explanation: MongoDB is the most popular NoSQL database, it stores data as a backend and helps frontend systems work.
Answer: MapReduce
Explanation: MapReduce combines a mapper and reducer, which facilitates users with an aggregation framework.
Answer: Collation
Explanation: The row key in Google Bigtable can’t use frequently updated identifiers as a data type to store data efficiently.
Answer: Polymorphism
Explanation: Using a dynamic scheme, MongoDB can provide the schemas before you can add data to them.
Answer: Relational Data
Explanation: NoSQL databases are popular for storing unstructured data, whereas Relational Data is highly structured.
Answer: MongoDB is a NoSQL Database
Explanation: MongoDB is a highly scalable database that prefers JSON files for data exchange.
Answer: 12-byte Hexadecimal Value
Explanation: The default value for the _id field is a 12-byte hexadecimal value.
Answer: NoSQL
Explanation: NoSQL can store data efficiently and speed up the LFC system.
Answer: Dynamic Schema
Explanation: Dynamic schema means that documents in the same collection do not need the same fields or structure. Common areas in a collection’s documents may hold different types of data.
Answer: Short
Explanation: Redis keys are more minor in size, and short data types can easily store these keys.
Answer: Frequently Updated Identifiers
Explanation: The row key in Google Bigtable can’t use frequently updated identifiers as a data type to store data efficiently.
NoSQL stands for “Not Only SQL, ” a database designed to handle a massive amount of unstructured data, semi-structured data, and relational data. It existed when other traditional databases failed to provide seamless data services and proved highly scalable and flexible for handling big data produced in the real world. This allows MNCs, like Google and Facebook, to deliver cloud-based services to store data in real time.
To track data records in NoSQL, below are the steps:
A. First, we must embed all stored data in a user object.
B. Then, we can create the user id credentials to log in with that.
C. After using login credentials, we can give comments value with a list of comments; this will display the result.
Below are some essential features of NoSQL:
Aggregate-oriented databases play a significant role in reducing the computation and managing the storage over the cluster. As the name suggests, aggregate databases are data collections that interact with other data as a single unit with the help of key-value properties and ACID operations.
Both NoSQL and relational database systems (RDBMS) are used to store the data, but they are different in the following ways:
Yes, the concept of normalization is used in NoSQL to prevent data redundancy and losses. In NoSQL, Apache Cassandra is a famous normalization-based database that stores data in a series of tables depending upon the fields.
Below are the types of NoSQL databases:
Examples: Redis, Riak, and Oracle NoSQL.
For Example: ArangoDB, CosmoDB, and MongoDB.
Examples: Neo4j, Oracle NoSQL, and Graph Base.
Some of the examples are: Apache Cassandra, ScyllaDB, and Microsoft Azure Cosmos DB.
Eric Brewer proposed the CAP theorem in early 2000, which acts as the three most reliable guarantees for a database. The CAP stands for:
Yes, using NoSQL in an Oracle-based database to record data is possible. With the help of the external table function, records in the NoSQL database can be retrieved or queried by the Oracle database.
The idea behind the term Polyglot Persistence is to write an application in mixed languages so that one can handle a particular problem in the correct language rather than trying to solve multiple issues in a single language. This concept is used while storing the data in NoSQL. To create a safer type of data storage system, developers choose multiple data storage systems to store various data and protect the single data storage systems. Hence, polyglot persistence is nothing but the use of multiple data storage technologies to handle different types of data storage needs.
IBM developed Big SQL, a fast-performing database used to store enterprise data. Big SQL supports MPP( Massive parallel processing) to securely handle large amounts of data.
Impala is famous for its ability to perform low-latency queries. Impala offers parallel processing in database technology just after the successful handling of big data by the administrator. The use of parallel processing decreases the fetching time and enhances the system’s performance.
NoSQL has a flexible data model for managing semi-structured and unstructured data easily.
NoSQL database is preferable in the following situations:
In NoSQL, the terminology BASE stands for:
Scaling is nothing but the ability to increase the capacity of a database system to store a huge amount of data without affecting data performance.
Databases can be scaled either:
Vertically: Vertical scaling is the process of increasing the hardware capacity(e.g., CPU, RAM) by inserting more resources into existing machines, which helps to enhance the server’s processing power.
OR
Horizontally: Horizontal scaling enhances the database capacity by increasing the number of servers, distributing data, and adding more machines.
Denormalization is not a reverse of normalization. Instead, it is a data optimization technique applied after normalization. Denormalization adds redundant data to multiple tables and helps us to ignore the expensive joins in a relational database.
Below are some limitations or disadvantages of the NoSQL database:-
This blog covers most of the frequently asked interview questions on NoSQL for freshers that could be asked in data science, Data Analyst, and big data developer interviews. Using these interview questions as a reference, you can better understand the concept of NoSQL and start formulating practical answers for upcoming interviews. The key takeaways from this NoSQL blog are:
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