This article on SQL and NoSQL comparison will throw light on the debate on advantages and limitations on each. Ever since the buzz of NoSQL database evolved in storing data into the NoSQL databases, I thought of exploring both the concepts to reach out to its depth. And it took me some time to figure out things that actually lead to the evolution of the NoSQL database.
Well, it all comes down to the quest of providing the best possible experience to the end-users in a quick, real and connected way. Database developers are trying to optimize things to yield better performance as the technology in the storage department is changing drastically.
Basics of SQL and NoSQL database:
What is SQL database
Talking about SQL database, the basic concept is that; it has is a Relational database. Yes! SQL database is a relational database. So what exactly is a relational database? A relational database strictly uses relations (frequently called as tables) to store data. A relational database matches data by using common characteristics found in the dataset. And the resulting group is termed as Schema.
A relation (table) in a relational database is divided into a set of rows and columns. A Tuple stands for a row in a database table that is retrieved using a query.
So how does SQL help?
SQL (Structured Query Language) is a programming language that is used to manage data in relational databases. Microsoft SQL Server is the best example. Microsoft SQL Server is a relational database that is used to store and retrieve data by applications either on the same computers or over the network.
Basic features of SQL server
- A relational database is a set of tables containing data fitted into predefined categories.
- Each table contains one or more data categories in columns.
- Each row contains a unique instance of data for the categories defined by the columns.
- The user can access data from the database without knowing the structure of the database table.
Limitations for SQL database
Scalability: Users have to scale relational databases on powerful servers that are expensive and difficult to handle. To scale a relational database it has to be distributed on multiple servers. Handling tables across different servers is chaos.
Complexity: In SQL server’s data has to fit into tables anyhow. If your data doesn’t fit into tables, then you need to design your database structure that will be complex and again difficult to handle.
What is NoSQL database?
In the past few years, the ”one size fits all“ – thinking concerning data stores has been questioned by both, Science and web companies, which has to lead to the emergence of a great variety of alternative databases. The movement as well as the new datastores are commonly subsumed under the term NoSQL.
The basic quality of NoSQL is that it may not require fixed table schemas, usually avoid join operations, and typically scale horizontally. Academic researchers typically refer to these databases as structured storage, a term that includes classic relational databases as a subset.
NoSQL database also trades off “ACID” (atomicity, consistency, isolation, and durability). NoSQL databases, to varying degrees, even allow for the schema of data to differ from record to record. If there doesn’t exist schema or a table in NoSQL, then how do you visualize the database structure? Well here is the answer
No schema required: Data can be inserted in a NoSQL database without first defining a rigid database schema. As a corollary, the format of the data being inserted can be changed at any time, without application disruption. This provides immense application flexibility, which ultimately delivers substantial business flexibility.
Auto elasticity: NoSQL automatically spreads your data onto multiple servers without requiring application assistance. Servers can be added or removed from the data layer without application downtime.
Integrated caching: In order to increase data through and increase performance advance NoSQL techniques cache data in system memory. This is in contrast to SQL database where this has to be done using the separate infrastructure.
Describing the architecture of data storage in NoSQL, there are three types of popular NoSQL databases.
- Key-value stores. As the name implies, a key-value store is a system that stores values indexed for retrieval by keys. These systems can hold structured or unstructured data.
- Column-oriented databases. Rather than store sets of information in a heavily structured table of columns and rows with uniform-sized fields for each record, as is the case with relational databases, column-oriented databases contain one extendable column of closely related data.
- Document-based stores. These databases store and organize data as collections of documents, rather than as structured tables with uniform-sized fields for each record. With these databases, users can add any number of fields of any length to a document.
The image shows the difference between three of them.
Advantages of NoSQL database
1) NoSQL databases generally process data faster than relational databases.
2) NoSQL databases are also often faster because their data models are simpler.
3) Major NoSQL systems are flexible enough to better enable developers to use the applications in ways that meet their needs.
SQL NoSQL Comparision and Conclusion:
SQL and NoSQL have been great inventions over time in order to keep data storage and retrieval optimized and smooth. Criticizing any one of them will not help the cause. If there is a buzz of NoSQL these days, it doesn’t mean it is a silver bullet to all your needs. Both technologies are best in what they do. It is up to a developer to make better use of them depending on the situation and needs.
If you are looking to explore NoSQL, you can download Microsoft NoSQL Azure whitepaper.
Go here if you want to learn about the difference between MySQL and SQL Server.