In the highly competitive world of software and web development, choosing the right database management system (DBMS) is crucial for any application's success. The choice of database directly impacts the performance, scalability, and overall efficiency of data handling. A database management system (DBMS) stores, manages, protects, and organizes data in a structured manner. It allows data engineers and analysts to read, create, update, and delete data for different project purposes. Now the question is which are the best databases that offer high-level scalability, flexibility, and security to access and use data. Depending on the domain and scale of your application, you can choose from the 2 most popular database types - SQL and NoSQL.
Both databases have pros and cons, making them different from each other and suitable for different use cases. Understanding the pros and cons of SQL and NoSQL can help you make the right choice that aligns with your project's specific needs. In this blog, we are going to discuss the meaning, and pros and cons of both databases to help you choose the best option.
What is SQL Database?
SQL Database, also known as relational databases, uses Structured Query Language to define and manipulate data. It follows a structured approach to store data using relational databases like MySQL, Oracle, PostgreSQL, and SQL Server. These databases consist of a set of tables with a fixed schema that includes and manages data classified by category. Each table consists of rows and columns corresponding to a particular category and contains the data from that category. The column represents a specific attribute of data, while a row represents a unique record. Using this, data engineers and analysts can easily use, manipulate, and update data records and perform high-level data analysis.
Pros of SQL Database
SQL databases offer various advantages that make them perfect for various applications, especially the ones that require structured data and strong consistency. Have a look at some of its important benefits:
ACID Compliance
SQL databases are ACID compliant due to the highly structured architecture of their relational database tables. This means they provide data integrity even after a system failure and, therefore, leave no room for error. They keep the tables in sync while ensuring transaction validity.
Standardized schema
Although SQL databases with standardized schemas and relational databases are more inflexible and difficult to adapt, they nonetheless offer various benefits. All data entered into the database must adhere to the known schema of connected tables (rows and columns). Some might find this limiting, but it's important for data consistency, compliance, security, and integrity.
Advanced Query Capabilities
SQL provides powerful querying capabilities that can perform extremely complex queries, including multiple tables, subqueries, joins, aggregations, etc. Also, as it is a standardized query language, the same SQL commands can be used across various relational database systems. This makes SQL databases suitable for analytical tasks and reporting.
Data security
In SQL databases, data is stored in tables that restrict outsider access to confidential information. Furthermore, it provides robust security features that improve the confidentiality of sensitive data and guarantee that only authorized individuals may access or modify it, such as role-based access control, user authentication, permissions, etc.
Data accuracy and integrity
SQL databases utilize a specified structure to maintain data consistency and integrity. The schema enforces standards for data types, constraints, and connections, making keeping accurate and dependable data easier. Moreover, relational databases use primary and foreign keys to prevent data redundancy, which improves the accuracy of data in SQL databases.
No code required
SQL is a simple, developer-friendly language that does not require coding. The database can be managed and queried using simple keywords in plain English, making it easy to learn, create, modify, and update.
Large user community
SQL is one of the most popular programming languages, which means it has a large and strong user community with countless promising expats who know the language well. They can share tips and best practices with data engineers and developers to sharpen their skills and collaborate. In case of errors or other problems, they can guide and help to find the right solutions.
Cons of SQL Database
While SQL databases offer many benefits, it also has certain limitations that make it less suitable for certain use cases or data types. Here are some of its main cons:
Cost
Relational databases are expensive to develop and maintain. First, you need pricey hardware and database development software, as well as a team of experts who can work on and maintain the system. Additionally, as data expands, so does the demand for increased processing capability, which may be met by adding RAM, SSD, or CPU at an additional cost.
Performance issues
One of the biggest problems with relational databases is that they become slower as they grow. As an organization grows, the amount of data generated increases. When this data is kept in a database and accessed by numerous users at the same time, the query response time decreases dramatically, reducing the database's performance. It demands a lot of processing power, and databases can't manage so many requests per second, which slows it down quickly.
Poor scalability
SQL databases have poor scalability; they are not ideal for horizontal scaling due to strict consistency requirements. They can only be scaled well vertically by upgrading the existing server's hardware. They cannot handle a high volume of queries and data, making it ineffective after a certain point when data becomes too much.
Rigidity
SQL has a fixed schema, which means it's inflexible to modify and update once it's in place. Therefore, the schema must be defined properly before use. Moreover, a significant amount of time and expertise must be dedicated to preliminary planning prior to bringing the database into production and executing it. This makes SQL databases invaluable if your data model is projected to change frequently.
What is a NoSQL Database?
NoSQL, as the name suggests, is the opposite of SQL, which means it is a non-relational database which does not require a fixed schema and is easily scalable. It does not store data in structured tables; instead, it stores it in separate documents in required formats like JSON files. The data is stored in tabular form like documents, graphs, key values, etc. It is useful for flexible schemas, especially when working with large amounts of complex data like real-time web apps. Some examples of NoSQL databases are MongoDB, Cassandra, Redis, HBase, etc.
Pros of NoSQL Database
NoSQL databases offer various advantages, especially for companies that require high scalability, flexibility, and development cycles. Have a look at some of its pros:
High Performance
NoSQL databases offer excellent performance, which outperforms SQL databases. It shows outstanding performance in delay in responding to requests and boosts the speed of data processing. Even when data engineers work with large volumes of data, it offers faster data operations, which ultimately enhances performance.
Query speed
NoSQL allows data engineers to run queries faster, even on large data sets. Moreover, even when the database grows, the speed and performance do not slow down as they don't require joins. Besides that, as NoSQL queries are denormalized there is no fear of data duplication, as a result lookups become easier making it faster for simple queries.
Scalability
Contrary to SQL, NoSQL offers high scalability by distributing data across many servers. When the number of records in one database outstrips the resources, additional servers or drives can be added to increase storage. It is designed to handle large datasets that can be scaled horizontally as well as vertically to accommodate more data. It offers flexibility for scaling a range of data growth types.
Flexibility
NoSQL does not require a predefined schema, making it capable of storing and combining multiple data types, unlike SQL, which can only store structured data. For example, it can also store photos, images, video files, data charts, etc. This quality makes it more versatile and valuable as compared to SQL databases.
Cost-effectiveness
NoSQL is cheaper than SQL in terms of setup and maintenance. It can be installed and run even on affordable low-resource devices, making data storage and management cost-effective. Moreover, it can be scaled up horizontally, which means the capacity can be expanded at less cost rather than upgrading the expensive software.
Cons of NoSQL Database
Like SQL, even NoSQL has several drawbacks that make it unsuitable for some use cases and project scope and type. Here are some disadvantages:
Immaturity and lack of support
NoSQL databases are relatively new to the market as compared to SQL databases, therefore it's not as feature rich and mature as SQL. Moreover, as it is new, it doesn't have a vast support community like SQL. This drawback makes it difficult to get help and advice from experts in times of undocumented issues and bugs. However, new features are added with every new update, making it suitable and versatile.
Data analysis challenges
Unlike SQL, which does not require any coding, NoSQL requires a certain level of programming expertise, making it inevitably unusable for certain companies. Moreover, some important BI tools do not work with NoSQL databases, which can challenge companies in handling and managing data.
Inefficiency with complex queries
Although NoSQL is flexible and can work with a variety of data, their querying is not that efficient. As there is a lack of standard databases to conduct complex queries, even the simplest ones require programming experience, making it crucial to hire costly data scientists with language experience.
Consistency
Data is readily available in NoSQL due to its distributed nature, but it's not necessary that the data will be consistent. Sometimes, queries might not return updated data; sometimes, when you enter repetitive data, it does or warns you, etc. This drawback causes the database to return different values consecutively, making it less consistent and reliable.
Conclusion
In conclusion, we can state that both SQL and NoSQL have their own pros and cons making them different from each other. Choosing between the two depends on your application needs, scalability and flexibility requirements, data structure and consistency expectations. If you need strong consistency along with complex querying capabilities you can go for SQL and if your requirements are scalability, flexibility and handling unstructured data, choose NoSQL. Both databases require skilled and experienced data analysts and engineers who have all the knowledge of the required database.
