Data drives the business world, and a significant amount of that data is unstructured. This implies that traditional relational databases can not cater to the needs of organizations seeking to store and manipulate this unstructured data. Companies are therefore relying on NoSQL Databases to manage their growing consumption and generation of everyday data.

NoSQL Databases are storage tools that allow you to manage data without the constraints of form and syntax. MongoDB, HBase, etc, are examples of NoSQL Databases that companies utilize to scale their business and replicate their vast datasets.

This article will introduce you to  NoSQL databases and discuss their types. It will also elaborate on the importance of these storage units and explain the 2 methods using which you can perform NoSQL data replication. Read along to learn more about NoSQL databases, data replication with NoSQL databases, and their use cases!

What is a NoSQL database?

NoSQL Data Replication: NoSQL Logo

NoSQL (Not only SQL) Databases are storage units that are not restrained by a fixed schema. These non-relational databases can store your data in any format and even provide you with easy scalability. NoSQL Databases are popular among data professionals who work with big data.

Since NoSQL Databases can manage information in a distributed form and process huge data volumes at a tremendous pace, Big Data-based applications use them to provide real-time functionalities. Therefore, companies like Google, Facebook, Amazon, and other huge tech giants leverage NoSQL Databases to manage their ever-increasing data.

The storage structure of a NoSQL Database works on a distributed architecture. This allows you to scale up your work horizontally using commodity hardware.  Moreover, the NoSQL Databases contain failover mechanisms that offer high Data Availability to your business.

NoSQL Data Replication is also a robust feature that allows you to seamlessly copy and store your structured, unstructured, and semi-structured data and prevent data losses in case of a server crash.

Types of NoSQL Databases

NoSQL Databases come in various forms and provide you with different approaches to data management and replication. All the NoSQL Databases present in the current market can be classified into the following 4 categories:

1. NoSQL Key-value Databases

The Key-value structure presents the most basic form of storing NoSQL data. This structure allows you to either:

  • Access the values stored against a key
  • Assign and store a value against a key
  • Delete a value stored against a key

The value is a small piece of data that you can store in the NoSQL Database without providing any details regarding its type or importance. Therefore, if your application uses a Key-value based Database, it needs to operate without any metadata. This storage facility is simple but offers great data access and manipulation performance. Furthermore, it is ideal for API-based applications. 

2. NoSQL Graph Databases

NoSQL Graph Databases can store your data in the form of entities and allow you to create relationships between these entities to facilitate faster access. The stored entities are known as nodes, and their relationships are called edges.

These edges have certain properties allowing you to traverse the stored data. Moreover, such edges contain directional significance, which dictates the structure of Graph-based storage. These directions help you to distinguish the hidden patterns among your nodes.

You can store your business data in a NoSQL Graph, and your teams can derive multiple interpretations from the structure and relationships present among edges and nodes. Since these relationships are not calculated while a Query is run, NoSQL Graph Databases offer high-speed processing.

The advantage of this structure is that traversing the established relationships in this type of database is a faster way of executing repeated queries. 

3. NoSQL Column Family Databases

Column-family NoSQL Databases store information in small data chunks related to each other and usually accessed simultaneously. This type of storage contains various columns bound by a row key. Each Column-family is equivalent to a row container of the RDBMS table which is accessible via keys (Primary and Foreign).

However, in Column Family NoSQL Databases, multiple rows can have different columns, and you can even add more columns to any row at any time interval. This allows you to let users access selective information at a time.

4. NoSQL Document Databases

The NoSQL Document Database is designed to facilitate flexible storage and fast processing of data in documents. Such databases store and retrieves data in the form of XML, BSON, JSON, and other similar formats. Document Databases mainly support self-describing data structures that are present as hierarchical trees and contain data as maps, collections, scalar values, etc.

NoSQL Document Databases mirror the functionality of Key-value Databases as the documents are stored in association with specific keys. However, in the NoSQL Documents, you can easily examine the value of keys, which is impossible in the Key-value Databases.

Reasons to Choose NoSQL Databases

NoSQL Databases are popular among Big Data professionals for the following reasons:

  • They improve the productivity of data engineers and developers by offering data storage with minimum syntax-based restrains. This implies programmers can store data in a format that is beneficial for their applications, unlike relational databases, which operate on a rigid syntax.
  • NoSQL Databases enhance the data access speed of vast data volumes by reducing latency and improving throughput.
  • The majority of NoSQL Databases are available as open-source tools. This implies you can download and test them seamlessly before starting any big project. This way, you can be sure of software compatibility and prevent the risk of future software crashes.
Replicate Data From NoSQL Databases like MongoDB in Minutes Using Hevo!

Hevo Data, an Automated No Code Data Pipeline can help you automate, simplify & enrich your data replication process in a few clicks. With Hevo’s wide variety of connectors and blazing-fast Data Pipelines, you can extract & load data from 150+ Data Sources like MongoDB NoSQL Database (including 50+ Free Sources) straight into your Data Warehouse or any Databases.

To further streamline and prepare your data for analysis, you can process and enrich raw granular data using Hevo’s robust & built-in Transformation Layer without writing a single line of code!

Get Started with Hevo for Free

Hevo is the fastest, easiest, and most reliable data replication platform that will save your engineering bandwidth and time multifold. Try our 14-day full access free trial today to experience an entirely automated hassle-free Data Replication!

Methods of NoSQL Data Replication

You can seamlessly set up your NoSQL Data Replication using the following two methods. Each of these would have its own advantages and disadvantages.

1. Master-slave Replication

This data replication in NoSQL creates a copy (master copy) of your database and maintains it as the key data source. Any updates that you may require are made to this master copy and later transferred to the slave copies.

Moreover, to maintain fast performance, all read requests are managed by the slave copies as it will not be feasible to burden the master copy alone. In case a master copy fails, one of the slave copies is automatically assigned as the new master.

Pros of Using Master-slave NoSQL Data Replication

The Master-slave approach for replicating your NoSQL Databases has the following advantages:

  • The Master-slave approach is extremely fast and it doesn’t operate on any performance or storage restrictions. Moreover, since read and update tasks are divided among master and slave copies, you can perform both operations in quick succession without facing any time delay.
  • You can use the Master-slave NoSQL Data Replication technique to split the data read and write requests and allocate them to different servers. This will further improve your data processing speed and efficiency.

Cons of Using Master-slave NoSQL Data Replication

  • This technique lacks reliability as it operates asynchronously. This implies that in cases the master copy fails, certain committed transactions will go missing, and no slave copy will contain that information.
  • The Master-slave technique does not support high scaling of Write requests. If you wish to scale such requests, you will require additional computational capacity on the master node.

2. Peer-to-Peer Replication

The Peer-to-Peer NoSQL Data Replication works in the concept that every database copy is responsible for updating its data. This can only work when every copy contains an identical format of schema and stores the same type of data. Furthermore, Database Restoration is a key requirement of this Data Replication technique.

Pros of Using Peer-to-Peer NoSQL Data Replication

  • Since the catalog queries are stored across multiple nodes, the performance of Peer-to-Peer NoSQL Data Replication remains constant even if your data load increases.
  • If a node fails, the application layer can commute that node’s read requests to other adjacent nodes and maintain a lossless processing environment and data availability.
  • The Peer-to-Peer technique for replication makes node maintenance easy as it allows you to take individual nodes offline for upgrade or maintenance without hampering the overall system performance.

Cons of Using Peer-to-Peer NoSQL Data Replication

The Peer-to-Peer NoSQL Data Replication technique comes along with the following drawbacks:

  • Modifying a particular row at multiple database nodes can cause data loss by triggering a conflict.
  • Replicating changes is costly in terms of latency in Peer-to-Peer replication. Furthermore, if an application requires real-time data relocation, you need to dynamically perform the challenging task of load balancing across different nodes.

Use Cases of NoSQL Databases

Now, since you have a strong grasp of NoSQL Data Replication and the various types of databases that it supports, it’s time to understand the real-life utility of such NoSQL Databases. The following use cases are the most popular applications of NoSQL Databases: 

  • Identity Verification & Fraud Detection
  • Catalog & Inventory Management
  • Providing Personalization & Recommendations

Identity Verification & Fraud Detection

Relational databases can allow you to analyze transactional data only. However, to implement effective measures of fraud detection and identity authentication, you need to dive deeper into Data Analysis.

This implies information other than transactions, such as demographic data, Customer Relationship Management data, historical data on shopping, etc., plays an important role in solving both these issues.

Therefore you need to rely on NoSQL Databases to accommodate data of different syntax and schema. Moreover, the flexibility of  NoSQL Databases will further enhance your Data Analysis and allow you to build strong fraud detection programs.

Catalog & Inventory Management

NoSQL Databases provide you with high Data Availability and also allow you to perform cost-effective scaling. This implies e-commerce organizations can make use of NoSQL Databases to store their ever-increasing product and marketing data. Moreover, such storage also allows them to easily access and update their inventory regularly.

The current market’s competition forces e-commerce companies to upgrade quickly and maintain availability. In such a situation companies can not afford website failure due to syntax constants or storage limitations. This is why e-commerce businesses rely on NoSQL Databases to market their various products online.

Discover Hevo’s efficient data pipelines with no maintenance required. Get a personalized demo and experience our top-rated, cost-effective ETL solution trusted by data engineers worldwide.

Providing Personalization & Recommendations

You can easily integrate Machine Learning with NoSQL Databases and use the historical record to provide accurate and helpful recommendations to your consumers. Moreover, since such databases can work with all types of data, you can ensure a personalized experience during a customer’s journey on your e-commerce website.

Furthermore, NoSQL databases can support you in maintaining historic records of customer care data which can be critical for developing new and improved products. 

Summing Up

The article introduced you to NoSQL Databases and explained their importance. It also explained the different types of NoSQL Databases available and listed the methods using which you can perform NoSQL Data Replication.

Moreover, the article elaborated on the various popular use cases of NoSQL Databases and how they can enhance your business. No SQL Data Replication is a popular and highly useful technique adopted by businesses in the current world.

Now, to run queries or perform Data Analytics on your raw data, you first need to export this data to a Data Warehouse. This will require you to custom-code complex scripts to develop the ETL processes. Hevo Data can automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Customer Management, etc.

This platform allows you to transfer data from 150+ sources to Cloud-based Data Warehouses like Amazon Redshift, Snowflake, Google BigQuery, etc. It will provide you with a hassle-free experience and make your work life much easier.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand.

Share your understanding of NoSQL Data Replication in the comments below!

Nitin Birajdar
Lead Customer Experience Engineer

Nitin, a seasoned professional with 9 years of experience, excels in ETL, Data Engineering, SAAS, and AI as a Customer Experience Lead. His expertise drives innovation and excellence, ensuring optimal solutions for diverse data challenges.

No Code Data Pipeline For Your Data Warehouse