Today, more than 4 billion people are using smartphones, tablets, and PCs. As a result, the amount of data produced each day is mind-boggling. Experts estimate that three quintillion bytes of data are currently being created each day. There are several reasons why we are building a lot of data today. One of those reasons is that we conduct more than half of our web searches via our smartphones and tablets. There are 5 billion searches conducted online a day.
Second, more than 3.7 billion people are using the internet. What many people do not know is that low data quality is costing Big Data companies more than $15 million yearly. Due to this, most companies are using the wrong business strategies as well as making poor decisions. This affects productivity and even creates mistrust between the brand and customers.
At our current pace and the accelerated growth of the internet and IoTs, it's projected that the amount of data will double. To manage this data, we need databases. There are hundreds of different databases available on the market. As a first-time application developer, choosing the right database is a daunting task. The good news is, we researched and narrowed it down to two databases - SQL and Non-SQL.
What is a SQL Database?
SQL database is a relational database that comprises tables that store structured data. The tables contain a collection of rows, also referred to as records, and columns referred to attributes. To manage and manipulate data in the tables, experts use SQL, a domain-specific language. This language comprises a set of commands that allow the querying of the database.
What you need to know is that SQL is not a programming language. But it allows the creation of procedural extensions that extend its functionality. The most famous examples of SQL databases include Oracle, Microsoft SQL Server, Access, and Sybase.
What is the Non-SQL Database?
A Non-SQL database is a non-tabular mechanism for storing and retrieving data. Unlike SQL databases, a Non-SQL database provides flexible schemas and scale, which allows for the storage of large amounts of data. It also provides for higher user loads. One of the most famous examples of a Non-SQL database is MongoDB. This is a document-oriented database that stores data in dynamic schemas.
Companies that use this type of database include Foursquare, eBay, and Craigslist.
Significant Differences between SQL and Non-SQL Databases
Relational vs. Non-Relational
An SQL database is a relational database. Data is usually organized in a structured way. The database stores data in a collection of tables. Since it's a relational database, the tables are generally related to each other through the use of primary and secondary keys.
When it comes to a Non-SQL database, this is a non-relational database. As such, it is document-based or comprises vast column stores. The non-relational database stores data in the form of collections that have no or few relations between them.
Because of its relational database model, SQL is a better option for apps such as accounting systems. These apps require multi-row transactions.
Structured vs. Unstructured Schema
An SQL database has a structured schema. How you may ask. Data is generally stored in N number of tables. Thanks to the tabular format, users can apply nested queries with even subqueries to insert, delete, or even create new tablets. For Non-SQL databases, they use an unstructured format to store data. This makes a Non-SQL database unfit for complex queries because you cannot use SQL to query a non-relational database.
Vertical vs. Horizontal Scalability
An SQL database is vertically scalable. What this means is that you can increase the load balance of servers. All one has to do is optimize the hardware. For example, you can increase RAM, processing power, or storage capacity.
Non-SQL databases are horizontally scalable. They are the opposite of SQL databases. Instead of adding hardware to improve the database's performance, you need to add more servers to your cluster. As such, the database system will be able to handle a large amount of traffic.
Hierarchical Data Storage
While SQL databases are best fit for complex queries, they are not fit for hierarchical data storage. This is despite the databases using the tabular form to store data.
On the other hand, Non-SQL databases are ideal for hierarchical data storage. This is because the non-relational database follows the key-value pair model of data storage. This is similar to JSON data. Due to this, Non-relational databases are usually preferred for large data sets, the kind used by Big Data companies.
To query a relational database, you can use SQL, a powerful language used to define and manipulate data. Versatile and safe, SQL allows users to make complex queries. The only problem with SQL is that it's restrictive. How you may ask. The language requires the user to use a predefined schema, and the data must follow the same structure.
Non-relational databases use UnQL or Unstructured Query Language. Unlike SQL, UnQL is more suitable for querying data stored in JSON format. The developers behind CouchDB and SQLite databases primarily developed this language.
SQL has been in existence for more than four decades. Developed in the 1970s, SQL language was created by IBM researchers. However, the language was not made available to the public until after a few years. Today, the SQL language is the standard language in relational database communication. As such, SQL vendors offer excellent support.
When it comes to NoSQL databases, there are few experts. Most Non-SQL databases are open source, and people have not explored the technology, unlike relational databases.
SQL databases have been around for more than 40 years. During this period, relational databases have become instrumental in helping businesses make better decisions. They have also been useful for multi transactional apps that require complex queries.
Due to the rise of Big Data, a new database management system was introduced. Non-SQL has proven to be popular among Big Data companies thanks to its dynamic schema for unstructured data. While non-relational databases are not suited for complex queries, they're fit for hierarchical data.
Sadly, most non-relational databases only offer community support. The good news is, big tech can hire experts for large scale deployment of Non-SQL databases. As a business or application developer, SQL is still a great choice.
Examples of SQL databases include MySQL Community Edition, MS SQL Server Express Edition, and Oracle Express Edition.
But if your company produces large, unstructured amounts of data, we recommend Non-SQL databases. Examples of Non-SQL databases include Redis, MongoDB, and CouchDB.