Pros and Cons of Using SQL vs NoSQL Databases

What is NoSQL Database?

Fundamentally, any database that does not have structured data and which is not relational can be referred to as a NoSQL database. Notably, NoSQL databases do not have data in the form of tables and do not follow a structured system of data storage and management. This means that these databases do not have any fixed system for extracting, storing and maintaining information or ‘values’ in datasets.

The data is stored in these databases in a non-tabular form with data types being dependent on the active data model. For instance, documents, graphs, key values and wide columns are some NoSQL data types. 

NoSQL databases are more scalable than traditional RDBMS and are used for working with massive amounts of data that experience concurrent operations with multiple users. NoSQL databases are particularly useful for enormous user loads, fundamentally being useful for big data that can be accessed and effectively used by a large number of users parallelly.

Some examples of NoSQL databases are DynamoDB, Mongodb, CouchDB, Orient DB, SimpleDB, FlockDB, Cassandra, Infinite Graph, Lotus Notes, CouchBase, HBase, Riak, Neo4J and Redis. However, we must take care to not confuse NoSQL databases with Hadoop or other file distribution systems that rely on nodes or clusters.

NoSQL databases are easy to scale and integrate with modern applications, thus making them a more preferred option in recent times. It is also comparatively easier for developers to make changes and use data from NoSQL databases in real-time during development. For instance, MongoDB Atlas allows developers to map data types such as documents to objects in the programming language of their choice while modifying the schema in real-time.

NoSQL databases work hand-in-hand with applications and grow along with the project. Developers can also choose to automate infrastructural operations and optimise performance in accordance with requirements with minimal data movement in a secure manner.

There are two important types of NoSQL databases:

• Document-oriented NoSQL Databases: For example, MongoDB and CouchDB.
• Graph Databases: For example, Infine Graph and InfoGrid.

Must Recommended Topic, Schema in DBMS

Fundamental Differences Between SQL and NoSQL Databases

One major thing that people get confused about is NoSQL databases do not literally mean ‘No SQL’ or ‘Non-SQL’. NoSQL refers to ‘Not only SQL’ and is a more flexible approach to Database management compared to traditional RDBMS. Fundamentally, the main difference between SQL and NoSQL databases is the ability of NoSQL databases for storing data in other formats than just relational tables. NoSQL databases also have the ability to work with massive amounts of data that is unstructured, as compared to SQL databases being effective (or efficient) with only structured data. 

However, when talking about the differences between SQL and NoSQL databases, these are not necessarily the advantages or disadvantages of these database systems. Sometimes, it is much easier to use one or the other depending on the nature of operations or the data type at hand. So, let us talk about what makes these two types of databases different.

Here are some key differences:

• SQL databases are table-based while NoSQL databases are generally document-based or graph-based. Some NoSQL databases even work on key-value pairs or wide-column stores.
   
• SQL databases have predefined schema while NoSQL databases are more flexible and have dynamic schema.
   
• SQL databases are vertically scalable while NoSQL databases are horizontally scalable.
   
• SQL databases are the best option when working with structured data while NoSQL databases can work with all types of data (even semi-structured and unstructured).
   
• SQL databases are great for complex queries with the use of SQL while NoSQL databases are not that great with queries of complex nature. NoSQL is a better fit for using attributed values or for working with a collection of documents. Meanwhile, SQL is highly suitable for extensive query operations.
   
• SQL databases focus on durability, consistency, isolation and atomicity while NoSQL databases focus on partition tolerance, availability and consistency.

Fundamentally, NoSQL databases either employ the use of complex data structures paired with keys or these databases attribute values to keys to form key-value pairs. Meanwhile, SQL databases simply employ collections of datasets that are segregated through records or tables and columns. NoSQL databases also support nested documents while SQL databases completely depend on tabular segregation. Now, let us get into SQL vs NoSQL pros and cons and SQL vs NoSQL performance.

Pros and Cons of SQL Databases

The main advantages of SQL databases are:

• Adjusted, standardised and affordable
   
• Availability of more SQL database-oriented product suites and integrations
   
• Existing for a longer time, thus having a larger community and more support systems behind them
   
• Operational atomicity
   
• Easy rollbacks and setups
   
• Compatibility when working with the right data types and information
   
• Efficient with complex queries and ongoing query operations

The main disadvantages of SQL databases are:

• Not efficient with large volumes of data
   
• Database execution can sometimes be challenging
   
• Complicated to use and SQL is more complex than modern document-oriented methods
   
• Not scalable enough, especially horizontally
   
• Lack of decentralisation and flexibility
   
• Only effective with structured data
   
• Requires more powerful hardware and better IT infrastructure
   
• Slow compared to modern NoSQL-based systems
   
• Not great for huge user loads or multiple concurrent operations
   

Must Read SQL Clauses

Pros and Cons of NoSQL Databases

The main advantages of NoSQL databases are:

• Decentralisation and adaptability
   
• Flexible and easy to integrate with applications or development pipelines
   
• More accessible and easy to use as a database
   
• Adjustable according to operational requirements without hampering active operations or with minimal data movement
   
• Enormous scalability and efficiency when working with big data or massive volumes of data
   
• Supports structured, unstructured and semi-structured data
   
• Can easily work on weaker hardware and simple IT architecture
   
• Supports a massive number of concurrent users

The main disadvantages of NoSQL databases are:

• Not effective with maintaining atomicity or accuracy, thus decreasing the trustworthiness of the information
   
• NoSQL databases are more unorganised and can face attribution problems
   
• Lack of standardisation
   
• Lack of smooth transmutation or institutionalisation across other NoSQL databases. This makes it extremely tough to change one’s setup or move to another database system
   
• Less support and fewer available frameworks to ensure a stable future for databases working on non-Linux systems
   
• Slower upgrades and almost nonexistent product suites other than the ones offered by the NoSQL database service providers.
  
  You can also read about the Multiple Granularity Locking.

Frequently Asked Questions

Is NoSQL faster than SQL?

Not inherently. NoSQL and SQL databases serve different purposes. Performance depends on the use case. NoSQL excels in scalability and flexibility, while SQL is structured for complex queries.

What is NoSQL example?

MongoDB is a popular NoSQL example. It's a document-oriented database, storing data in flexible, JSON-like BSON format, providing scalability and quick access to data.

Which database is NoSQL?

Examples include MongoDB, Cassandra, Couchbase. NoSQL encompasses various types like document-oriented, key-value, wide-column stores, and graph databases.

Why use a NoSQL database?

NoSQL databases are suitable for scenarios demanding scalability, flexibility, and quick data retrieval. They excel in handling large volumes of unstructured or semi-structured data.

Who should use NoSQL?

NoSQL suits projects with dynamic or evolving schemas, high-traffic web applications, real-time analytics, and scenarios where quick and flexible data retrieval is crucial.

Conclusion

With changing requirements of modern times, developers are now rapidly adopting NoSQL databases and recognizing the need for scalability and flexibility. SQL will always be important and SQL databases will always be used by a huge number of organisations. However, NoSQL systems are increasingly being incorporated into application development and other development pipelines due to the minimal data movement and real-time iterations. Also, with the advent of cloud computing and the need to distribute data across several servers and areas, NoSQL is slowly becoming the more preferred option. 

Data comes in all sizes and types, thus NoSQL provides the all-in-one solution to work with polymorphic, unstructured, and semi-structured data. SQL databases are great but they are the best option when working with structured data in a limited organisation environment with no need for future scaling.

Also Read - TCL Commands In SQL

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