In the 21st century, data surrounds us everywhere. Storage of data happens in many forms such as images, videos, texts, voice notes, graphs, etc. Storing data in huge amounts makes it vital for an increased RAM on our phone, laptops, and PCs for a better and faster performance.
In this context, we are storing data (and not just any data but ‘Big Data’!) Big Data has penetrated the term ‘NoSQL’ in the database management system. Earlier, Database Management System only included MySQL, highly using it for storing homogeneous data. Basically, it stored only structured data (i.e. data that has a fixed schema or form). But then this wasn’t enough to store ‘Big Data’. This lead to the introduction of NoSQL databases.
What is NoSQL?
Traditionally, databases store data in tables containing rows and columns which is structured data (much like a spreadsheet that you see in Excel). These are also called Relational Databases or SQL Databases. However, now we want to store data in any format. So NoSQL databases emerged as a new, wide variety of database technologies that stored unstructured data (this was a major drawback of traditional/relational databases).
Note: – However, NoSQL is schema-less. But this does not mean that these databases do not comply with any schema.
Why the need for NoSQL?
Limitations of Relational Databases
Relational databases store data in tables and have a fixed structure of each table. They impose a strict structure on how and what kind of data can be stored.
However, nowadays a lot of highly unstructured data (unstructured data comprises 80% of the data today) that needs to be stored or operated. Moreover, the designing of relational databases did not provide the required scalability and agility of Big Data. To enable this, we need a different database technology that can handle these sorts of “imperfections” in the data.
NoSQL databases exist in many types-
Broadly speaking, they use one of the following structures:-
- Document: As the name suggests, it stores information in a document. The exact definition of a document differs from database to database. However, each of these databases store data in one of the structured data formats such as BASON, JSON and XML, etc. E.g. – MongoDB and CouchDB.
- Graph: Graph databases store information in nodes, which can then be connected to other nodes. They make highly connected databases and complex queries easier and faster. The best way to visualize graph database is to think of Facebook. Consider your profile to be a node on Facebook. You connect to your friends (who are also nodes), forms a graph. E.g. – Neo4j
- Key: Value database – It is the simplified version of the more robust Document Database. Here, each entry is a simple key-value pair. It is the simplest and is easy to implement. But it is inefficient when you are only interested in querying or updating a part of value. E.g. –Voldemort, Redis.
- Wide – Column – Wide-column databases are a lot like Relational Databases. But instead of storing data in a row-oriented manner, they store data in a column-oriented manner. It makes certain operations much faster as compared to that of traditional databases. Of course, this works only on certain kinds of operations and may slow down other operations that row-oriented databases may perform faster. E.g. – Apache’s Cassandra.
Did You Know? Johan Oskarsson accidentally coined the term NoSQL at an event where NoSQL was the hashtag to organize the meeting.
Why would you go for NoSQL databases?
- Better at handling unstructured data.
- Ability to scale well, i.e., it can grow horizontal.
- Ability to grow vertical by storing data on different servers.
- Lower cost.
Interesting fact – Try Googling the full form of ‘NoSQL’? There is actually no full form or an appropriate meaning of it.
There are many features of NoSQL databases that have widened the field of the software industry to store and analyze unstructured data. However, these have become popular among web companies today with the use of a cluster of the cheaper server to handle large data and transaction volumes. Also, innovative enterprises and companies are investing a lot in the Internet of things (IoT) for developing new products with reduced costs.
What other kinds of NoSQL databases have you used? Do you think that these databases are truly helpful in nature?