SQL vs NoSQL Exact Differences and Know When To Use NoSQL and SQL

What are SQL and NoSQL and what is the exact difference between SQL vs NoSQL? Learn when to use these with the pros and cons of each.

When we say, ‘SQL vs NoSQL, the primary need becomes, to understand the basic meaning of both these terms.

Once we comprehend the meaning of SQL and NoSQL mean, then we would be able to move ahead with their comparison easily.

SQL Vs NoSQL Databases

What is SQL?

Structured Query Language, commonly abbreviated as SQL, is a domain-specific programming language that is used for storing, manipulating and retrieving data in RDBMS (Relational Database Management System).

It is mainly used for managing structured data where we have a relationship between various entities and variables of the data.

SQL

SQL consists of a various type of statements to query or handle the data stored in the databases.

These type of statements are further classified as shown below:

  • DDL (Data Definition Language): These are the Queries that are used for schema creation and modification. The common DDL commands in SQL include CREATE, ALTER, and DROP.
  • DML (Data manipulation language): This Query is used for performing select, insert, update and delete operations in the database. The common DML commands in SQL are SELECT, INSERT, UPDATE and DELETE.
  • DCL (Data Control Language): Such Queries are used to control access and provide authorization onto the database. The common DCL commands in SQL are GRANT and REVOKE.
  • TCL (Transaction Control Language): These queries are used for controlling and managing transactions to maintain data integrity. The common TCL commands in SQL include BEGIN, COMMIT, and ROLLBACK.

Further reading => Top SQL Interview Questions

What is NoSQL?

NoSQL (also refers to Not only SQL, non-SQL or non-relational) is a database which gives you a way to manage the data which is in a non-relational form i.e. which is not structured in a tabular manner and does not possess tabular relationships.

NoSQL

NoSQL is increasingly gaining popularity as it is being employed in big data and real-time applications. Their data structures are completely different from those of relational databases.

NoSQL is an alternative to conventional relational databases in which data is put in tables and the data structure is carefully designed before the database is created. It is mainly helpful for working with huge sets of distributed data. NoSQL databases are scalable, high performant and flexible in nature.

It can also deal with a wide variety of data models.

Types of NoSQL Databases:

Basically, there are four types of NoSQL databases.

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#1) Column: Wide column stores and arranges the data tables as columns rather than as rows.

They can query a large volume of data very quickly than the traditional databases. They can be employed for recommendation engines, catalogs, fraud detection, etc.

Examples: Cassandra, HBase, Google BigTable, Scylla, Vertica, etc.

#2) Document: Document databases, aka document stores and keeps the semi-structured data along with its description in the document format.

Each document has a unique key through which it is addressed. They are helpful for content management and mobile application data handling. They are widely used along with JSON and JavaScript. Document databases also offer an API and query language through which the documents can be fetched based on their contents.

Examples: Apache, MongoDB, MarkLogic, CouchDB, BaseX, IBM Domino, etc.

#3) Key-value: Key value databases have their data model based on an associative array (map or a dictionary) in which the data has represented a collection of key-value pairs. They are highly suitable for session management and caching in web applications.

Examples: Aerospike, Berkeley DB, Apache ignites, Dynamo, Redis, Riak, ZooKeeper, etc.

#4) Graph: In graph stores, data is organized as nodes and edges.

You can think of a node as a record and edge as a relationship between the records in the relational database. This model supports a richer representation of data relationships. They are useful for customer relationship Management systems, road maps, reservation systems, etc.

Examples: AllegroGraph, InfiniteGraph, MarkLogic, Neo4j, IBM graph, Titan, etc.

Difference Between SQL and NoSQL

SQLNoSQL
SQL databases are mainly relational database (RDBMS).NoSQL databases are mainly non-relational or distributed databases.
An aged technology.Relatively young technology.
SQL databases are table based in the form of row & columns and must strictly adhere to standard schema definitions.
They are a better option for applications which need multi-row transactions.
NoSQL databases can be based on documents, key-value pairs, graphs or columns and they don’t have to stick to standard schema definitions.
They have a well-designed pre-defined schema for structured data.They have the dynamic schema for unstructured data. Data can be flexibly stored without having a pre-defined structure.
SQL databases favors normalized schema.NoSQL databases favors de-normalized schema.
Costly to scale.Cheaper to scale when compared to relational databases.
SQL databases are vertically scalable. They can be scaled by increasing the hardware capacity (CPU, RAM, SSD, etc.) on a single server.NoSQL databases are horizontally scalable. They can be scaled by adding more servers to the infrastructure to manage large load and lessen the heap.
They are a good fit for complex queries as SQL has a standard interface for handling queries.
The syntax of SQL queries is fixed.
Not a good fit for complex queries as there is no standard interface in NoSQL for handling queries.
The queries in NoSQL are not as powerful as SQL queries.
It is called as UnQL, and the syntax for using the Unstructured query language will vary from syntax to syntax.
SQL databases do not suit well for hierarchical data storage.NoSQL databases suit best for hierarchical data storage as it follows the key-value pair method for storing the data.
From a commercial perspective, SQL databases are generally classified as open source or closed source.They are classified on the basis of the way they store data as key-value store, document store, graph store, column store, and XML store.
SQL databases properly follow ACID properties (Atomicity, Consistency, Isolation & Durability).NoSQL databases properly follow Brewers CAP theorem (Consistency, Availability, and Partition tolerance).
Adding new data in SQL database requires some changes to be made like backfilling data, altering schemas.New data can be easily inserted in NoSQL databases as it does not require any prior steps.
Excellent vendor support and community support is available for all SQL databases.Only limited community support is available for NoSQL databases.
Best fit for high transaction-based applications.You can use NoSQL for heavy transactional purpose. However, it is not the best fit for this.
Not suitable for hierarchical data storage.Suitable for hierarchical data storage and storing large data sets (E.g. Big Data).
Example of SQL databases: MySQL, Oracle, MS-SQL, SQLite.Examples of NoSQL databases: MongoDB, Apache CouchDB, Redis, HBase.

SQL vs NoSQL Security

Primarily, it is essential to know the meaning of database security. For a database to store the information in a secured manner, it is required to provide confidentiality, integrity, and availability which is collectively known as CIA.

Confidentiality means that only the authorized users or systems can access the data, Integrity is the accuracy and consistency of the data over its lifespan and Availability means that the data should be available whenever it is needed.

Most of the enterprise-based relational or SQL databases like Oracle and MSSQL have strong security features integrated into them. They abide by the ACID properties which ensure secure and reliable database transactions.

RDBMS also has features like role-based security, access-control via user-level permissions, encrypted messages, support for row and column access control, etc. However, these security features do need a significant licensing fee and affect the speed of data access.

For an application which is handling a huge volume of unstructured data, we can’t solely use SQL based databases. For Example, Social networking websites. These applications have two main requirements i.e. scalability and availability. This requirement is served by NoSQL databases.

However, NoSQL databases security is not as robust as relational databases security. NoSQL does not strictly follow ACID properties. The one in NoSQL is known as the BASE (Basically available, soft state, eventually consistent) properties.

Instead of being consistent after every transaction, it is okay here for the database to be in a consistent state eventually. It may not be the case that you will always see the current data in NoSQL databases. You may be seeing the data as per last taken snapshot and a simultaneous transaction can interfere with each other.

This inherent race condition is a risk that is imposed by NoSQL databases.

Unlike SQL databases, the NoSQL databases have very few inbuilt security features in order to allow faster data access. They lack confidentiality and integrity attributes. Also, as they don’t have a fixed and well-defined schema, you can’t segregate the permissions.

Hence, as NoSQL databases don’t provide strong security features at their end, you will have to rely upon the security features of the application which is accessing the data. NoSQL databases are an easier target for security attack when compared to the relational databases.

Further Reading => How to Test and Prevent SQL Injection Attacks

When to Use NoSQL?

Given below are the use cases where you should prefer using NoSQL databases:

  • To handle a huge volume of structured, semi-structured and unstructured data.
  • Where there is a need to follow modern software development practices like Agile Scrum and if you need to deliver prototypes or fast applications.
  • If you prefer object-oriented programming.
  • If your relational database is not capable enough to scale up to your traffic at an acceptable cost.
  • If you want to have an efficient, scale-out architecture in place of an expensive and monolithic architecture.
  • If you have local data transactions that need not be very durable.
  • If you are going with schema-less data and want to include new fields without any ceremony.
  • When your priority is easy scalability and availability.

When to Avoid NoSQL?

Enlisted below are some pointers that would guide you on when to avoid NoSQL.

  • If you are required to perform complex and dynamic querying and reporting, then you should avoid using NoSQL as it has a limited query functionality. For such requirements, you should prefer SQL only.
  • NoSQL also lacks in the ability to perform dynamic operations. It can’t guarantee ACID properties. In such cases like financial transactions, etc., you may go with SQL databases.
  • You should also avoid NoSQL if your application needs run-time flexibility.
  • If consistency is a must and if there aren’t going to be any large-scale changes in terms of the data volume, then going with the SQL database is a better option.

One should also keep in mind that NoSQL databases won’t support structured query language. The querying language may vary from one database to another.

Pros and Cons of Each

Enlisted below are the various Pros and Cons of SQL as well as NoSQL.

SQL Pros:

  • It is highly suitable for relational databases.
  • Has a predefined schema which is helpful in many cases.
  • Normalization can be greatly used here, thus it also helps in removing redundancy and organizing data in a better way.
  • Transactions in SQL databases are ACID compliant, thereby guarantees security and stability.
  • Follows well-defined standards like ISI and ANSI which are accepted worldwide.
  • Code-free.
  • Unbeatable speed in retrieving database records with great ease.
  • Uses single standardized language i.e SQL across different RDBMS.

SQL Cons:

  • The process of interfacing is complex.
  • As SQL is an object, it occupies space.
  • Handling Big data is very costly as you will have to increase the hardware for scaling.
  • When a table is dropped, the view becomes inactive.

NoSQL Pros:

  • Capable of handling big data.
  • As it is schema-less and table free, it offers a high level of flexibility with data models.
  • It is a low-cost database and the open source NoSQL databases provide very affordable solutions to small enterprises.
  • Easier and low-cost scalability. You don’t need to increase the hardware for scaling. You just need to add more servers to the pool as NoSQL is schema-free and built on distributed systems.
  • Detailed database modeling is not required here. Hence it saves time and effort.

NoSQL Cons:

  • The benefits of NoSQL come at the cost of relaxing ACID properties. NoSQL offers only eventual consistency.
  • Relatively less community support.
  • Lacks standardization, unlike SQL, which in turn creates some issues during migration.
  • Inter-operability is also a concern in the case of NoSQL databases.

Conclusion

We learned the difference between SQL vs NoSQL in detail here. The choice of the database will depend upon your preferences, business requirements, volume, and variety of data.

NoSQL databases are gaining large popularity these days due to their capacity to integrate big data, low cost, easy scalability, and open source features. However, it is still a relatively young technology and lacks standardization, unlike SQL. Lack of ACID compliance is also a concern with NoSQL.

Hope this article would have immensely brushed your knowledge on the concept of SQL and NoSQL.