NoSQL Databases and Its Types: A Comprehensive Guide 101

on Database Management Systems • October 29th, 2021 • Write for Hevo

Today we are living in the Digital Era and Terabytes of data are being generated every month by all of us. This data may be in the form of text, pictures, numbers, binary codes, videos, graphs, etc. All the organizations are making use of their user data, product data, marketing data, etc to understand their businesses better and make data-driven decisions. This data is stored in databases. SQL databases were conventionally used to deal with structured data. But now data has become more complex and unstructured.

NoSQL Database is attracting users from all over the world due to its exceptional behavior and Big Data distributed processing capabilities for unstructured data. In this article, we will discuss in detail NoSQL databases and their types.

Table of Contents

What is NoSQL Database?

NoSQL stands for Not only SQL. NoSQL Databases are also known as non-relational databases that don’t require a fixed schema. Users can create documents with flexible schema and can scale up evenly without much of a stretch. NoSQL information bases are largely utilized for BigData and ongoing applications. NoSQL database processes information in a distributed manner and can oblige tremendous volumes of data.

Internet giants like Facebook, Google, Amazon use NoSQL databases heavily to deal with Terabytes of data daily.

As NoSQL Database uses distributed storage, it is easy to scale them up horizontally with commodity hardware. In the RDBMS world, the system tends to go slow when the volume of the data increases and could be tackled by scaling up the existing hardware. However, this process is expensive and inefficient. An alternative to this problem is distributing the data load to separate commodity hardware whenever the load increases.

Easy of scaling for NoSQL Databases.
Image Source: Guru99

Simplify Data Analysis with Hevo’s No-code Data Pipelines

Hevo Data, a No-code Data Pipeline helps to integrate data from 100+ sources to a Data Warehouse/destination of your choice to visualize it in your desired BI tool. Hevo is fully-managed and completely automates the process of not only loading data from your desired source but also transforming it into an analysis-ready form without having to write a single line of code.

Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using a BI tool of your choice.

GET STARTED WITH HEVO FOR FREE

Check out what makes Hevo amazing:

  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
  • Minimal Learning: Hevo with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  • Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
  • Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
  • Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.

Simplify your data analysis with Hevo today!

SIGN UP HERE FOR A 14-DAY FREE TRIAL!

History of NoSQL Databases

Handling SQL Databases are a time-consuming and costly task. Developers were the cost to the company rather than storage. Back in the late 2000s, NoSQL Databases emerged that changed the game of creating complex and difficult manage data models to avoid data duplication. NoSQL Databases are the perfect replacement for decreasing storage costs and increasing Developers’ costs. It optimizes the daily data management activities.

Due to the decline in prices of Data Storage, a sudden surge in the demand for storage and query increased. The data came in all shapes and sizes i.e., from structured and semi-structured to polymorphic data. Defining Schema for data for all the huge volumes of data in advance in SQL databases is next to impossible. That is where NoSQL Databases handled all the demands for storing unstructured data. It helped developers store data and provide them greater flexibility.

At that time Cloud Computing also came into action and the need to host applications and data on public Clouds increased. Developers wanted to distribute the data across multiple servers to make their applications and data available all the time anywhere. NoSQL Databases helped them manage all the data hassle-free.

Features of NoSQL Databases

NoSQL Databases offer numerous features over traditional databases. We have listed a few of the most popular features of NoSQL Databases.

1. Schemaless Tables 

NoSQL Databases are schema-less and can store heterogeneous data from the same domain easily. Users can quickly load complex schemas and heterogeneous data in the same NoSQL documents or tables.

2. Non-Relational Structure 

NoSQL Databases don’t rely on relational models, and it doesn’t store the data in flat fixed schemas. It also doesn’t support complex features like query language, integrity-joins, ACID operations, etc. The above-listed points make the NoSQL Database popular among the BigData and real-time fields.

3. Simple API Controls 

NoSQL Databases offer easy-to-use API interfaces to allow low-level data manipulation. They are very well versed with REST endpoints.

4. Distributed Computing

NoSQL Databases offer distributed processing of queries along with auto-scaling and failover mechanisms.

NoSQL databases offer distributed processing services.
Image Source: Guru99

Types of NoSQL Databases

There are four different categories of NoSQL Databases: 

Types of NoSQL Databases
Image Source: Guru99

Let’s discuss each of them in detail. 

1. Document Databases

Document Databases use key-value pairs to store and retrieve data from the documents. A document is stored in the form of XML and JSON. A typical example of the document database is shown below:

Document Databases
Image Source: Guru99

The above figure shows that the Document database contains data in JSON (or XML) format and can contain varying schema. The Documents can be nested and indexed for faster querying.

Document databases allow developers to restructure their Documents based on their application requirements which may change over time. In contrast, in the RDBMS world, database administrators are required to restructure the database schemas.

Examples of Document databases are – MongoDB, OrientDB, Apache CouchDB, IBM Cloudant, CrateDB, BaseX, and many more.

2. Key-Value Stores

Key-value Stores are the simplest type of NoSQL Database. It uses keys and values to store the data. The attribute name is stored in ‘key’, whereas the values corresponding to that key will be held in ‘value’.

In Key-value store databases, the key can only be string, whereas the value can store string, JSON, XML, Blob, etc. Due to its behavior, it is capable of handling massive data and loads.

The use case of key-value stores mainly stores user preferences, user profiles, shopping carts, etc.

DynamoDB, Riak, Redis are a few famous examples of Key-value store NoSQL databases.

3. Column-Oriented Databases

Column-oriented databases store the data in a set of columns known as column families. That means that whenever a user wants to run queries for a smaller number of columns, they can read those columns directly without consuming memories corresponding to all data. The working of the Column-oriented database is based on the concept of the BigTable paper by Google. Below schematics shows how values are stored on Column-oriented databases:

Column-Oriented Databases - NoSQL Databases
Image Source: Guru99

HBase, Cassandra, HBase, Hypertable are NoSQL query examples of column-based databases.

4. Graph Databases

Graph databases form and store the relationship of the data. Each element/data is stored in a node, and that node is linked to another data/element. A typical example for Graph database use cases is Facebook. It holds the relationship between each user and their further connections. 

Graph databases help search the connections between data elements and link one part to various parts directly or indirectly.

Graph Databases - NoSQL Databases
Image Source: Guru99

The Graph database can be used in social media, fraud detection, and knowledge graphs. Examples of Graph Databases are – Neo4J, Infinite Graph, OrientDB, FlockDB, etc.

When Should NoSQL be Used?

One should always know when to use a NoSQL Database. A few factors are listed below:

  • To manage huge volumes of data.
  • Managing modern applications paradigms like microservices and real-time Streaming.
  • Need to store structured and semi-structured data.
  • Fast-paced Agile development.
  • Need to scale-out architecture.

Difference between RDBMS and NoSQL

There are many differences between Relational Database Management Systems (RDBMS) and NoSQL Databases. The core difference is how the data is modeled in both of the Databases. A few key differences between RDBMS and NoSQL are listed below: 

  • RDBMS is a relational Database, while NoSQL is a distributed database.
  • RDBMS is vertically scalable which means servers have to be added and power has to be increased which makes scalability through RDBMS Databases quite expensive. NoSQL Databases are horizontally scalable which means it needs to add more machines only.
  • RDBMS has a fixed schema that makes it possible to insert data in a uniform format. It makes the data redundant and helps get the primary and foreign keys to fit data in the tables. In NoSQL databases, there is no need to have a schema. One can add data in structured as well as semi-structured which makes them more flexible than RDBMS Databases.
  • RDBMS has stored procedures to manage and understand data whereas NoSQL Database does not have any stored procedures which makes it difficult for users to identify patterns.

Advantages of NoSQL Databases

Let’s understand some of the advantages of NoSQL Databases:

  • NoSQL database is optimum for processing massive volume data with distributed processing. 
  • NoSQL database supports failover mechanisms and ensures high availability.
  • NoSQL database provides easy replication along with horizontally scalable capability. 
  • NoSQL database is capable of handling structured, semi-structured, and unstructured data.
  • NoSQL databases can be installed on commodity hardware and can form clusters for distributed processing.
  • NoSQL database offers flexible schema and can be changed at runtime without service downtime.  

Disadvantages of NoSQL Databases

In the above sections, we have discussed a lot about NoSQL databases and their benefits. However, there are certain limitations to the NoSQL database, which we have to look upon. Below are the few listed limitations:

  • NoSQL databases have limited query capabilities as compared to RDBMS. 
  • NoSQL databases don’t offer any RDBMS capabilities like consistency and ACID transactions.
  • Most of the NoSQL databases use key-value pairs to store the data. Hence it isn’t easy to maintain as the volume increases.
  • NoSQL databases are new to the markets and can be challenging for RDBMS programmers to switch to these technologies.
  • Most of the NoSQL databases are open source and are a restricted choice for enterprises. 

Conclusion

In this blog post, we have discussed in-depth NoSQL databases, their types, and their advantages and disadvantages. NoSQL databases are getting popular among enterprises due to their exceptional properties. 

Integrating and analyzing data from a huge set of diverse sources can be challenging, this is where Hevo comes into the picture. Hevo is a No-code Data Pipeline and has awesome 100+ pre-built integrations that you can choose from. Hevo can help you integrate data from multiple sources and load them into a destination to analyze real-time data with a BI tool. It will make your life easier and make data migration hassle-free. It is user-friendly, reliable, and secure. Check out the pricing details here.

VISIT OUR WEBSITE TO EXPLORE HEVO

Want to take Hevo for a spin?

SIGN UP and experience the feature-rich Hevo suite first hand.

Share your experience with NoSQL Databases in the comments section below!

No-code Data Pipeline for your Data Warehouse