Most Popular NoSQL Databases

There are many different NoSQL databases available, each with its own unique set of features and capabilities. Some of the most popular NoSQL databases include:

MongoDB

MongoDB is a popular NoSQL database that is based on the document store model, which means that data is stored in documents that are similar to JSON objects. This allows for the efficient representation and manipulation of complex data structures and relationships.

Cassandra

Cassandra is a NoSQL database that is based on the column store model, which means that data is organized into columns rather than rows. This allows for fast and efficient data retrieval, especially for large datasets.

Redis

Redis is an in-memory data store that is often used as a cache or message broker. It is known for its low latency and high performance, making it a popular choice for real-time applications and in-memory databases.

Couchbase

Couchbase is a document-based NoSQL database that is designed for high-performance and scalability. It is also known for its full-text search capabilities and its ability to handle unstructured data.

AWS DynamoDB

AWS DynamoDB is a fully managed NoSQL database service provided by Amazon Web Services (AWS). It is known for its scalability and performance, and it’s built to handle high-traffic, real-time applications.

Cosmos DB

Cosmos DB is Microsoft’s globally-distributed, multi-model database service. It’s very popular for its scalability, performance and multiple data models support ( Document, Key-value, Graph, Column-family)

Elasticsearch

Elasticsearch is a powerful search engine based on the Lucene library. It is a distributed, JSON-based search and analytics engine designed for handling large amounts of data.

HBase

HBase is also a NoSQL database that is based on the key-value store model, which means that data is organized as a set of keys and values. This allows for fast and efficient data access and retrieval, and is well suited for applications that require real-time data access.

These are some of the most popular NoSQL databases among developers and industry practitioners, and their popularity often reflects the specific needs and use cases that they are best suited for. It’s important to understand your own needs and requirements, and to test and evaluate the different options before choosing a specific database for your application.

Types of NoSQL Database

There are different types of NoSQL databases, including the following:

Document store

Document store NoSQL databases store data in documents that are similar to JSON objects. This allows for the efficient representation and manipulation of complex data structures and relationships. Examples of document store NoSQL databases include MongoDB and CouchDB.

Column store

Column store NoSQL databases store data in columns rather than rows. This allows for fast and efficient data retrieval, especially for large datasets. Examples of column store NoSQL databases include Cassandra and HBase.

Key-value store

Key-value store NoSQL databases store data as a set of keys and values. This allows for fast and efficient data access and retrieval, and is well suited for applications that require real-time data access. Examples of key-value store NoSQL databases include Redis and DynamoDB.

Graph database

Graph database store data as a network of nodes and edges, which allows for the efficient representation and manipulation of complex data relationships. Examples of graph databases include Neo4j and ArangoDB.

Wide-column store

Wide-column store NoSQL databases store data in columns, but the columns can be dynamically added or removed, which allows for more flexibility and scalability compared to traditional column store databases. Examples of wide-column store NoSQL databases include Bigtable and Apache HBase.

Advantages of NoSQL Database

Scalability and flexibility

One of the main advantages of NoSQL databases is that they are highly scalable and flexible, which means that they can easily handle large volumes of data and support a large number of users and applications. This is particularly useful for organizations that experience sudden spikes in traffic or data volume.

Improved performance

NoSQL databases can have improved performance compared to traditional relational databases, especially for large datasets or applications that require real-time data access. This is because NoSQL databases are optimized for fast and efficient data retrieval and manipulation, and are not limited by a fixed schema.

Support for unstructured and semi-structured data

NoSQL databases are well suited for handling unstructured and semi-structured data, which is data that does not have a fixed schema or data that is not easily organized into rows and columns. This is particularly useful for applications that require the integration of different data types and sources, such as multimedia data or data from multiple sources.

Ease of use and development

NoSQL databases are typically easier to use and develop as compared to traditional relational databases, especially for developers who are not familiar with SQL. This can reduce the time and resources required to develop and maintain applications that use a NoSQL database.

Cost savings

NoSQL databases can help organizations to reduce costs, since they do not require the upfront investment in hardware and infrastructure that traditional relational databases do. Additionally, organizations only pay for the resources they use, which can help to control costs and avoid overspending.

Disadvantages of NoSQL Database

Limited support for SQL

One of the main disadvantages of NoSQL databases is that they do not support SQL, which is the standardized and widely used language for managing and querying data in relational databases. This can limit their compatibility with other systems and applications that use SQL, and may require developers to learn and use specialized NoSQL query languages.

Limited support for ACID transactions

NoSQL databases typically do not support ACID (Atomicity, Consistency, Isolation, Durability) transactions, which are a set of properties that guarantee the integrity and consistency of data in a database. This can limit their ability to handle complex data manipulation operations, such as data aggregation or data mining.

Limited vendor support

NoSQL databases are not as widely used as traditional relational databases, which means that they may have limited vendor support and resources compared to other database models. This can make it more difficult to find support and expertise for NoSQL databases.

Potential vendor lock-in

Organizations that use a NoSQL database may be dependent on their database vendor, which can create vendor lock-in and limit their ability to switch to another database in the future.

Compatibility issues

NoSQL databases may not be compatible with other database models, which can limit their interoperability and integration with other systems and applications.

Use Cases of NoSQL Database

NoSQL databases are a popular choice for many modern applications because they offer several benefits over traditional relational databases.

So, when to use a NoSQL database? Here are common use cases for NoSQL databases:

1. Storing and processing large amounts of data, such as in the case of big data applications: NoSQL databases are designed to scale horizontally, which means they can easily handle large volumes of data without sacrificing performance.
2. Storing and managing unstructured data, such as documents, images, and videos: NoSQL databases are typically more flexible than relational databases, which makes them well-suited for handling unstructured data.
3. Building real-time, high-performance applications, such as mobile and web applications: NoSQL databases are generally faster and more efficient than relational databases, which makes them a good choice for applications that require quick response times.
4. Mobile and IoT applications: NoSQL databases are often used to store and process data from mobile and Internet of Things (IoT) devices, due to their ability to handle a high volume of read and write operations in real-time.
5. Enabling rapid development and deployment of applications: Because NoSQL databases are typically more flexible and scalable than relational databases, they can make it easier and faster to develop and deploy modern applications.
6. Supporting cloud-native architectures and applications: NoSQL databases are often used in cloud-based applications because they are designed to be distributed and scalable, which makes them well-suited for the dynamic nature of cloud environments.

Which is the Fastest NoSQL Database?

When it comes to performance, NoSQL databases have some inherent characteristics that make them particularly fast, such as horizontal scaling and distributed architecture. However, the specific performance of a NoSQL database will depend on a variety of factors, including the size and complexity of your data, the number of concurrent users and requests, and the specific implementation and configuration of the database.

With that said, some NoSQL databases are known for their high performance and are commonly used in high-traffic and high-performance applications. Some examples of NoSQL databases include:

• Redis: Redis is an in-memory data store that is often used as a cache or message broker. It is known for its low latency and high performance, making it a popular choice for real-time applications.
• Aerospike: Aerospike is a distributed NoSQL database that is optimized for high performance and low latency. It is designed for high-traffic, real-time applications and it’s known for his high performance and scalability.
• Cassandra: Cassandra is a highly-scalable, distributed NoSQL database that is optimized for read and write performance. It’s been used in high-performance applications that require low-latency data access, and it’s known for it’s linear scalability.
• MongoDB: MongoDB is a document-based NoSQL database that is known for its high performance and scalability. It also provides built-in sharding and automatic balancing of data, making it a good choice for high-traffic, real-time applications.

Keep in mind that the specific performance of a NoSQL database will depend on a variety of factors and it’s always recommended to test and validate the performance of the database under your specific use case, workload and data size.

It’s also worth to note that, performance is not the only factor to take into account when choosing a database, you should also consider the specific requirements of your use case, your expertise with the database and your team skills to manage and maintain the database.

More to Read

• Relational Database Benefits and Limitations
• Relational Vs Non Relational Database
• 13 Examples of Relational Database
• Relational Database Vs. Object-Oriented Database
• 9 Types of Databases
• Distributed Database
• Operational Database
• Personal Database
• Graph Databases
• Centralized Database

Relational databases have been around since the late 1970s and are one of those technologies people seem to take for granted these days. These were originally created in order to help businesses store their financial records more efficiently on mainframe computers.

What is Relational Database?

Relational databases are also referred to as SQL databases, relational database management systems (RDBMS), and business intelligence platforms. Relational databases are built to work with large amounts of data and are commonly used by companies in the following scenarios:

• Large corporate institutions:
• Companies with multiple departments and divisions. They have multiple data stores for information used by different teams within the department.

Relational databases are also called Relational Database Management Systems (RDBMS) or SQL databases. They are the most common type of database used in business. The most popular of these have been Microsoft SQL Server, Oracle Database, MySQL, and IBM DB2. These relational databases are used mostly in large enterprise scenarios. These are vital for businesses because they enable companies to store, access, update and manage information and have a clear path to the various departments that need this data.

In relational databases, tables related to one another are linked and queries on the database can produce relations between these tables. Non-relational databases separate these relations into different sets of documents, which are then stored together in a flexible data format. This means that non-relational databases can be used for OLTP just as well as relational databases can.

Relational Database Users

Following users are benefitted from relational database systems

Database Administrators: They perform the duty of monitoring the performance and keeping the maintenance of the system. They are also responsible for database integrity and security and other related issues of the system.

Software Developers/Programmers: They create and design the database. The programmers interact with the database through programming languages.

End-User: They perform the task of fetching data/information from the system through commands and are also able to insert, update and delete the data.

Relational Database Benefits

Relational databases work with structured data. They support ACID transactional consistency and provide a flexible way to structure data that is not possible with other database technologies. Key features of relational databases include the ability to make two tables look like one, join multiple tables together on key fields, create complex indexes that perform well and are easy to manage, and maintain data integrity for maximum data accuracy.

The relational database is a system of storing and retrieving data in which the content of the data is stored in tables, rows, columns, or fields. When you have multiple pieces of information that need to be related to one another then it is important to store them in this type of format; otherwise, you would just end up with a bunch of unrelated facts and figures without any ties between them.

There are many benefits associated with using a relational database for managing your data needs. For instance, if you want to view all the contacts in your phone book (or other types) then all you would need to do is enter one query into the search bar and instantly see every contact listed there. This saves time from having to manually go through.

The relational database benefits are discussed briefly.

1 – Simplicity of Model

In contrast to other types of database models, the relational database model is much simpler. It does not require any complex queries because it has no query processing or structuring so simple SQL queries are enough to handle the data.

2 – Ease of Use

Users can easily access/retrieve their required information within seconds without indulging in the complexity of the database. Structured Query Language (SQL) is used to execute complex queries.

3 – Accuracy

A key feature of relational databases is that they’re strictly defined and well-organized, so data doesn’t get duplicated. Relational databases have accuracy because of their structure with no data duplication.

4 – Data Integrity

RDBMS databases are also widely used for data integrity as they provide consistency across all tables. The data integrity ensures the features like accuracy and ease of use.

5 – Normalization

As data becomes more and more complex, the need for efficient ways of storing it increases. Normalization is a method that breaks down information into manageable chunks to reduce storage size. Data can be broken up into different levels with any level requiring preparation before moving onto another level of normalizing your data.

Database normalization also ensures that a relational database has no variety or variance in its structure and can be manipulated accurately. This ensures that integrity is maintained when using data from this database for your business decisions.

6 – Collaboration

Multiple users can access the database to retrieve information at the same time and even if data is being updated.

7 – Security

Data is secure as Relational Database Management System allows only authorized users to directly access the data. No unauthorized user can access the information.

Relational Database Limitations

Although there are more benefits of using relational databases, it has some limitations also. Let’s see the limitations or disadvantages of using the relational database.

1 – Maintenance Problem

The maintenance of the relational database becomes difficult over time due to the increase in the data. Developers and programmers have to spend a lot of time maintaining the database.

2 – Cost

The relational database system is costly to set up and maintain. The initial cost of the software alone can be quite pricey for smaller businesses, but it gets worse when you factor in hiring a professional technician who must also have expertise with that specific kind of program.

3 – Physical Storage

A relational database is comprised of rows and columns, which requires a lot of physical memory because each operation performed depends on separate storage. The requirements of physical memory may increase along with the increase of data.

4 – Lack of Scalability

While using the relational database over multiple servers, its structure changes and becomes difficult to handle, especially when the quantity of the data is large. Due to this, the data is not scalable on different physical storage servers. Ultimately, its performance is affected i.e. lack of availability of data and load time etc. As the database becomes larger or more distributed with a greater number of servers, this will have negative effects like latency and availability issues affecting overall performance.

5 – Complexity in Structure

Relational databases can only store data in tabular form which makes it difficult to represent complex relationships between objects. This is an issue because many applications require more than one table to store all the necessary data required by their application logic.

6 – Decrease in performance over time

The relational database can become slower, not just because of its reliance on multiple tables. When there is a large number of tables and data in the system, it causes an increase in complexity. It can lead to slow response times over queries or even complete failure for them depending on how many people are logged into the server at a given time.

Final Words

Relational databases are traditionally used to manage data in an organization. The main benefits of using relational databases are that they can be easily queried, allow for the use of stored procedures to manipulate data, and provide a consistent database design. They also have limitations when it comes to high volume transactions or large amounts of data storage, the issue of speed can arise.

Either these are benefits that attract you or the limitations that keep you at a distance. You can easily decide whether the relational database is for you or otherwise.

Further Reading

• Important Aspects of Relational Databases
• 9 Types of Databases
• Distributed Database
• Personal Database
• Centralized Database