What is a SQL Database?
SQL or relational databases are structured. They can be compared to phone books that stores phone numbers and addresses. It organizes structured data fields in defined columns. SQL is a programming language that is used by software engineers to design rational databases. Some examples of SQL database include MySQL, Oracle, Sybase and IBM DM2. These databases help execute queries, recover data and edit data. Editing data includes updating, deleting or creating new records.
NoSQL or non-relational databases are document oriented. They store the data like file folders, i.e. they hold everything, from a person’s address or phone number to their Facebook likes, shopping preferences, etc. It doesn’t incorporate the table model; the data can be stored in a single documented file. Hence, the data can be found easily but it cannot be categorized into fields like a relational database does. For example, Hadoop is an open source computing and data analysis platform that processes huge amounts of data in the cloud and is popular with NoSQL database stacks.
Advantages of SQL
- Simple yet powerful JOIN clause – a single command can retrieve related data stored across multiple tables
- Fit naturally into venerable software stacks, including LAMP and Ruby-based stacks – they are understood and widely supported if at all you run into problems
- Restricts access of a table so that nobody can insert the rows into the table
- Improved vertical performance so horizontal scalability is no longer a necessity
- View the data without storing data into the object
- No need to write a lot of codes
Advantages of NoSQL
- Ease of access for app developers
- NoSQL databases use APIs which allow developers to execute queries without having to learn SQL or understand the database system unlike relational databases that have a relationship with applications written in object oriented programming languages
- Rapid development – can make frequent updates to the data structure
- Cloud-based storage is an excellent cost-saving solution
- Sets no limits on the types of data you can store together – allows you to add different new types as your needs change
So, when would using NoSQL make sense?
Following are the instances when using NoSQL makes sense:
- Document Database solution CouchDB sums up the distinction between RDBMS and Document Databases.
- When the data is stored in key-value pairs – NoSQL database should be used. Redis, Voldemort and Dynamo are well-known key value stores.
- NoSQL should be used for softwares that have data or columnar database present. Examples for graph database include Neo4J and InfiniteGraph and columnar database include Cassandra and HBase.
- A NoSQL database sets no limits on the types of data you can store together. It allows you to add different new types as your needs change.
- When data is provided from a third party source, a NoSQL database is an application for statistics and/or reports generation.
- Using commodity (affordable, smaller) hardware on-site or in the cloud saves you the hassle of additional software. NoSQL databases such as Cassandra are designed to be scaled across multiple data centers out of the box without a problem.
When would using SQL make sense?
- ACID Compliancy protects the integrity of the database by stating how transactions interact with the database. For an E-commerce and financial applications, an ACID-compliant database is preferable.
- It would also make sense to use SQL if your data structure is not changing often.
So, which one is better – SQL or NoSQL?
So now that we’ve got a download on SQL and NoSQL database, you will need to assess if you require a relational or non-relational database management system. The idea that both these databases are in competition is not true – remember, that most companies use them concurrently.
If your data structure needs are changing and growing fast every minute, you need NoSQL; whereas, if you don’t have a changing structure and have a moderate growth rate, you must opt for SQL.
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