Relational or NoSQL

NoSQL

Not all data is relational and sometimes relational data benefits by being stored in a way optimized for the use case. There are many alternatives to relational databases that could be a better fit for your particular business need. Wide column, document, graph, key-value. Types of nosql db’s

Relational

Relational databases store data organized as table structures. Tables can be linked with each other based on a defined relation. That way users can access the data in relation to another piece of data.

Benefits

NoSQL

01

Data model optimized for the use case

NoSQL databases give you the possibility of choosing the best tool for the job. If your data is not relational, or the usage patterns don’t fit the way RDBMS work, you still have plenty to choose from. E.g. wide column Cassandra, document MongoDB, graph OrientDB or key-value Redis.

02

Support for semi-structured and unstructured data

The amount of unstructured data is growing. Relational databases with their traditional approach of storing normalized data might become a bottleneck for your project and moving to a NoSQL store could be a better approach.

03

Easily scalable with high availability and performance

Many NoSQL stores are created with scalability and performance at its roots. Easy sharding and replication gives the ability to easily scale out helping your system with both performance and availability.

Relational

01

Data Consistency

Data consistency is achieved through transactions that describe a sequence of operations as a single unit of work. If consistency rules of a database are violated, the entire transaction will be rolled back.

02

Overall Maturity

Relational databases have over 50 years of history. The relational model is well-known and understood by software engineers and SQL is well known by data analysts.

03

Reduced Redundancy

Data redundancy is reduced through the process of normalization. This allows to store less data and to have a clearer database schema design.

When to use

NoSQL

NoSQL databases are a great fit when dealing with large amounts of unstructured data

When the structure of data doesn’t fit the flat normalized model of relational databases.

When there’s need for high availability and the eventual consistency is not a problem

Relational

An RDBMS is a great fit for transaction-oriented systems such as customer relationship management tools, accounting software, and e-commerce platforms.

Great fit for structured data

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