Compare SQL and Nosql

SQL or Structured Query Language is a standardizes programming language mostly used for managing relational databases, With these data bases you can perform many different task and operations in the data base. Database administrators regularly use SQL for writing data integration scripts and data. Its also used by data analysts to set up and run analytical queries. “The uses of SQL include modifying database table and index structures; adding, updating and deleting rows of data; and retrieving subsets of information from within a database for transaction processing and analytics applications. Queries and other SQL operations take the form of commands written as statements -- commonly used SQL statements include select, add, insert, update, delete, create, alter and truncate.”

When someone is referring to a nonrelational database they are referring to a NoSQL database. NoSQL databases are built for specific data models and have flexible schemas for building modern applications. NoSQL uses a variety of data models, including documents, graphs, key-value, in-memory, and search. These types of databases are greatly used for specific applications that required large data volume, low latency, and flexible data models, which are done by relaxing some of the data consistency restrictions of other databases. A major disadvantage of NoSQL is that the community is not as well defined. The NoSQL community is new and lacks the maturity of the SQL user base.

Now Let’s Compare SQL and NoSQL. In terms of data storage SQL uses a relation model with rows and columns. Rows contain the information about a data entry and the columns separate all the data points. Lie stated previously NoSql uses a host of databases, each with different options for data storages. The key ones are document, graphs, and columnar. As far as flexibly for SQL,” Each record conforms to fixed schema, meaning the columns must be decided and locked before data entry and each row must contain data for each column”. (dataconomy.com) This can be amended, but you would have to take your database offline to alter it. For NoSQL information can be added whenever you want and each row doesn’t have to contain data for each column. Scalability in SQL is vertical. Meaning the more data, you have the bigger your server will need to be. In NoSQL scaling is horizontal. This means multiple servers can be cheap or a cloud instance making it more cost effective.

As far as I think SQL will still be relevant in the big data world, I do. Even though NoSql is rising many enterprises are used to SQL and it can be a hassle to switch over. Not only that but it would take time and money to train and get use to a new system. In the end the choice between NoSQL and SQL depends on the complex business of an organization and the volume and variety of data it uses.