SQL vs NoSQL
When it comes to choosing a database for modern systems there comes a situation whether to choose SQL or NoSQL. There are few people will suggest going with SQL and the some other will suggest going with NoSQL especially in recent days. Both of them have their unique features therefore it’s up to looking after the data requirements of the application to decide whether to choose SQL or NoSQL.So let’s have a look at how both of these differ from each other.
SQL Database
SQL is also known as a relational database is still the most used one. It uses structured query language to define, manipulate and retrieve data. Here the data structure is fully table-oriented where data are stored in a table format where each record is stored in rows while their attributes are stored in columns. The user has to define the data structure which means the data type and domain of each data attribute in a template called schema and it’s pretty easy to understand as well. This is also helpful in handling complex queries.
NoSQL Database
When it comes to the NoSQL database it’s an upcoming database which is still behind SQL on a usage basis but not a bad option to use nowadays. Its data structure is a contrast to SQL where the data can be stored in an unstructured manner without a predefined schema and there are many options to store our data like column-oriented, document-oriented, graph-based, or key-value based structures are available to go with.
The Differences….
The structural differences between these two lead to their key differences. Due to its schema-based structure, the SQL is more restrictive and safe when it comes to data integrity but when it comes to altering any changes or deleting a table then that would be not easy here due to the dependency between the tables and its static schema nature. Meanwhile, in NoSQL, it gives the flexibility of using unstructured data so the user doesn’t need to worry about the data types and the schema is dynamic which means the user can alter the data structure on the go. SQL can help handle complex queries while NoSQL is not good enough in that aspect.
When it comes to scalability SQL is vertically scalable where we can upgrade a single server by adding more resources(Eg: RAM, CPU..)while NoSQL is horizontally scalable where we can add more servers to a single database to handle additional traffic loads by splitting it across several servers. So NoSQL can be a better option when it comes to handling large or ever-changing datasets.
The SQL follows the ACID(Atomicity, Consistency, Isolation, and Durability) properties while the NoSQL follows the CAP(Consistency, Availability and Partition tolerance) theorm. Actually, this one difference will give you a glance idea about which DB will suit your requirements.
The Tools….
After you have decided the database that you are going to use then the next thing you have to choose is an appropriate database management tool. Some popular SQL databases are MySQL, PostgreSQL, Oracle, and Microsoft SQL Server. Some of the popular NoSQL database examples MongoDB, include Redis, RavenDB Cassandra, BigTable, HBase, Neo4j, and CouchDB.The above tools are on-premise software that means we can download it in our PC and use it but apart from these, there are a few cloud-based database tools also available which are provided by cloud service platforms like AWS(Eg: RDS, AURORA), Google cloud(Eg: Cloud SQL, Cloud spanner) and Microsoft Azure(Eg: Azure Database for MySQL, PostgreSQL, and MariaDB). And also the databases like MongoDB, Cassandra, and Redis have their own cloud service to host databases. These cloud-based databases are useful in terms of scalability, real-time data sharing, cost-effectiveness, and many more.
Therefore these tools also have some distinct features between them. So we can be more specific in our selection depending on the features that we would like to have for our database.
Conclusion
So when it comes to choosing the right database for your system is completely depends on your data requirements like how’s the data structure looks like, how the querying should happen, the data integrity, the scalability of your data by keeping the future developments in mind and many more. Therefore it can’t be a quick decision to choose a database on the go, we have to think about plenty of things before we choose the right one.