What is NoSQL? NoSQL Tutorial Guide for Beginner

In the early 1970s, flat file systems were used to store the Company data. The biggest problem with the flat file system was that each Company implement their own flat files. There were no standards to store and access data from flat files.

To overcome this issue, relational databases came into existence. But relational databases also get a problem later that it could not handle the voluminous data. To manage every tough problem, NoSQL databases were developed finally.

In this blog, we will discuss the NoSQL database fundamentals in detail, its features, types, and advantages, etc. The topics to be covered in the blog include:

• What is NoSQL?
• Why NoSQL?
• Quick History of NoSQL
• Features of NoSQL
• Types of NoSQL Databases
• Query Mechanism tools for NoSQL
• What is the CAP Theorem?
• Eventual Consistency
• Advantages of NoSQL

What is NoSQL?

Carl Strozzi introduced the term NoSQL in 1998 for his open source file-based databases. Traditionally, SQL or relational databases were used to store or retrieve data for future insights while NoSQL database encompasses a wide range of database technologies that can store structured, semi-structured, unstructured, or polymorphic data together.

• NoSQL or “Not SQL” is a new set of databases emerged in the recent past as an alternative to relational databases.
• it is the non-relational data management system that does not require a fixed schema, it is easy to scale, and it avoids joins.
• It is used for big data, distributed data stores, and real-time web apps. For example, Companies like Facebook, Twitter, or Google collect terabytes of data almost every day.

Why choose NoSQL Databases?

The increased use of social media has grown user-driven data rapidly that needs to be managed, analyzed, and archived properly. Additionally, other data sources like GPS, sensors, automated trackers, and monitoring systems also produce a huge amount of data regularly. The huge data set has introduced the challenges of data storage, data management, data analysis, etc. Moreover, it becomes semi-structured and sparse. In the case of RDBMS, there is a need for upfront schema and relational references.

To resolve these problems related to semi-structured or unstructured data, a range of new database products has emerged during the last few years. The new class of database products consists of column-based data stores, key-value pair databases, and document databases, etc. When used together, these databases are called NoSQL consist of diverse products each having a unique set of features and propositions.

Other than this, NoSQL databases can be scaled out easily when compared to SQL databases. The load is distributed among multiple hosts as shown below whenever load increases. In the next section, there is a detailed idea of how SQL and NoSQL databases are different from each other.

RDBMS

NOSQL

Data is stored in a relational model, with rows and columns. A row contains information about an item while columns contain specific information, such as 'Model', 'Date of Manufacture', 'Color'. Follows fixed schema. Meaning, the columns are defined and locked before data entry. In addition, each row contains data for each column. Supports vertical scaling. Scaling an RDBMS across multiple servers is a challenging and time-consuming process Atomicity, Consistency, Isolation & Durability(ACID) Compliant

Data is stored in a host of different databases, with different data storage models. Follows dynamic schemas. Meaning, you can add columns anytime Supports horizontal scaling. You can scale across multiple servers. Multiple servers are cheap commodity hardware or cloud instances, which make scaling cost-effective compared to vertical scaling Not ACID Compliant

A quick history of NoSQL Database

• 1998 - Carl Strozzi introduced the term NoSQL in 1998 for his open source file-based databases.
• 2000 – Graph database was launched.
• 2004 – Google Big Table was launched.
• 2005 – CouchDB was launched.
• 2007 – Amazon Dynamo was launched.
• 2008 – Facebook open source Cassandra projects were proposed.
• 2009 – NoSQL databases were introduced again.

Features of NoSQL database

Non-Relational

• NoSQL databases never follow the relational database models.
• It never provides a table with fixed column records.
• It works with self-contained aggregates.
• It does not require any data normalization or object-relational mapping.
• There are no complex features like relational databases.

Distributed Computing

• It is possible to execute multiple databases in a distributed manner.
• It offers fail-over capabilities and auto-scaling features.
• It can be used with all programming language, or there is no standard query to use with NoSQL databases.
• It provides eventual consistency.
• It provides no synchronous replication among distributed nodes.
• It enables maximum distribution and less coordination among data nodes.

Schema-Free

• NoSQL databases either have relaxed schemas or it is schema-free.
• It does not require any definition for the schema of the data.
• It offers heterogeneous data structures for the same domains.

Simple API

• It offers easy to use interface for data storage and data query.
• It allows low-level selection methods and low-level data manipulation.
• It uses text-based protocols with HTTP and JSON.
• It has no standard-based query language.
• It is a web-enabled database running as internet-facing services.

NoSQL Database Types you should know

There are four classes of NoSQL databases with their unique attributes and limitations. You should understand each of them in depth first and choose the best one that suits your requirements the most. Let us see each of them one by one.

1). Key-value pair based

This database is designed to manage heavy loads and a lot of data gracefully. It stores data in key-value pairs where each key is unique and value can be anything like object, string JSON, etc. Here is one quick example of the database given below. It is the most basic type of database that can be used as collections, arrays, dictionaries, etc. It helps developers to store the schema-less data. It works best for shopping cart content.

Read: Microsoft Power BI Tutorial For Beginners

2). Column-based NoSQL Database

This database is column-oriented where each column is treated separately, and values are stored contiguously. Here is the simple example of how column-based NoSQL database looks like: It works best for aggregation queries like SUM, Count, MAX, MIN, AVG, etc. It helps to find data quickly in columns. This database is majorly used for managing catalogs, data warehouse, BI projects, CRM, or library, etc.

3). Document-Oriented NoSQL Database

It stores and retrieves the data as key-value pair, but the value is stored in documents in XML or JSON formats. A database itself understands or queries the data. In the diagram, you can see a table where data is stored in row and column format. And the right-hand side is covered by documents where data is stored in JSON format. Here, you don’t have to define columns which makes it more flexible as compared to relational databases. It is mostly used for blogging platforms, CRM systems, or real-time analytics, etc. it is used for complex transactions that require multiple operations against varying aggregate functions.

4). Graph-based NoSQL Databases

This database stores the entity and defines the relationship among different entities. The stored entity is named as the node, and the relationship is defined as the edge. Each node and edge must have a unique identifier. Here, tables are multi-relational in nature, not loosely connected. Traversing relationship is much faster in NoSQL databases when compared to relational databases. It is mostly used for logistics, networks, and spatial data.

Query Mechanism tools for NoSQL Database

The data retrieval mechanism in NoSQL database is REST-based  the value is retrieved based on key/ID with the GET resource. Document stores the most difficult queries as they use the key-value pair to store the data. For example, Couch DB define views with the MapReduce.

What is the CAP Theorem?

This theorem is given by the Brewer which states that it is not possible for distributed data stores to give more than two out of total three guarantees. These are consistency, partition tolerance, and availability.

1). Consistency:

The data should remain consistent even after the execution of an operation, it means once data is written, any future read request should be able to access the same data. For example, once you update the status of an order, the client should be able to check the same data.

2). Partition Tolerance:

If communication among servers is not stable even then the system should be able to work properly, it is called the partition tolerance. For example, when the server is divided into multiple partitions, they may or may not communicate together. If one part of the database is unavailable even then other parts should not be affected.

3). Availability:

Read: How to Clear SQL Server Transaction Log File with DBCC Shrinkfile

The database should be highly responsive and available without any downtime.

Eventual Consistency

The term eventual consistency means multiple data copies are available on different machines to get higher availability and scalability. If some changes are made to one file, it should automatically be reflected other replicas. Data replication is not instantaneous because a few copies are updated frequently and a few over time. But you have to make sure content is the same for all replicas. Hence, the name of this phenomenon is given as eventual consistency.

BASE: Basically Available, Soft state, Eventual consistency

• Here basically available means DB is available all the time as per the assumption of CAP theorem.
• Soft state means the state of a system may change without an input.
• Eventual consistency means system become consistent over time.

Advantages of NoSQL Database

The desired technical characteristics for NoSQL database are given as below.

A). Primary and Analytic Data Source Capability

The first criteria for any NoSQL solution are that it must serve as the primary or active data source that receives data from different business apps. It should act as the secondary data source or analytical database to enhance the overall functionalities of business apps. Further, it should be capable of integrating with different types of data like structured, semi-structured, or unstructured. Additionally, it can execute complex queries too.

B). Big Data Capability

NoSQL databases are good with Big data, and they can be scaled quickly to manage voluminous data from terabytes to petabytes. Additionally, it delivers high performance for data velocity, data complexity, and the data variety.

C). Continuous Availability

NoSQL database is always available without any single point of failure. All nodes in the cluster can read request even if some machine is down. It can replicate data among different physical machines within a data center. It avoids hardware outages too.

Read: Top 50 Datastage Interview Questions and Answers

D). Multi-Data Center Capability

Business enterprises need highly distributed databases that are spread across multiple data centers or graphical locales without any performance issues. The solution includes the ability to handle multiple data centers without concerning the overall occurrences of read and write operations. A good NoSQL database supports multiple data centers and provides configuration options to maintain a proper balance between consistency and performance.

E). Separate Cache layer is not required

A good NoSQL database uses and distributes data among different participating nodes. It does not have a separate cache layer to store the data. The memory cache of multiple participating nodes stores data quickly for immediate I/O access. It eliminates the problems of synchronizing cache data with the persistent database. In this way, it supports higher scalability with fewer management issues.

F). Cloud-Ready

The adoption of cloud platforms is increasing daily by leading enterprises worldwide. This is the reason why every robust platform must be cloud-ready. NoSQL databases like MongoDB are cloud-ready able to work in a cloud setting when necessary. It supports the hybrid solution when one part of the database is hosted within the enterprise, and another part is hosted in the cloud.

G). High Performance and Scalability

NoSQL databases can enhance performance by adding multiple nodes to the cluster. Usually, the performance of a database system goes down with additional nodes to a cluster. However, a good NoSQL database increases performance for both read and write operations when new nodes are added, and performance gains are linear in nature. Here, we have listed the major benefits of the NoSQL database but there a few more as discussed by enterprises like easy to implement, easy to use, supports multiple languages & platforms, thriven open source community, etc.

Summary

The concept of NoSQL databases became popular with internet giants like Google, Amazon, Facebook, etc. who produce voluminous data daily. It is schema-free, avoids joins, and easy to scale when required.

The different types of NoSQL database can handle structured, semi-structured and unstructured data properly with equal effect. It makes any database highly available, consistent without a single point of failure.

Looking at multiple benefits and features of NoSQL databases, it is clear that they are certainly better than SQL or relational databases or more demanded by enterprises recently. To learn more about NoSQL database, join our SQL certification program and become a database master now.

Read: Difference Between SQLite and MySQL