![]() ![]() Lately, databases like MongoDB have found some success in breaking this barrier. Most NoSQL Databases support only eventual consistency and are hence not a great choice for transactional operations. NoSQL Databases achieve this by compromising consistency and referential integrity. ![]() NoSQL Databases do well in scenarios where sub-second response time for high data volume is required. NoSQL Databases are great at scaling horizontally and partition tolerance is built into their foundation. This helps in defining the database very close to the UI layer or where the data will be actually used or reported. NoSQL Databases recommend data to be stored in a format in which it will be frequently accessed. Since there is no particular structure enforced by the database, they are also not very good at join queries. This means data attributes can be added on the fly without changing the structure of the entire table or adding redundant elements to the rest of the rows. NoSQL Databases are great at storing semi-structured or non-structured data since they don’t enforce a concrete schema for tables. What are NoSQL Databases? 4 types of NoSQL Databases. This means Relational Databases are not very good at handling a large amount of data since the data they have to be stored in a single system or need constant babysitting because of their limitations when it comes to multi-node operation. It is safe to say that most Relational Databases prioritize consistency and availability over partition tolerance. Sharding leads to increased costs and requires close management. But none of them are as elegant as their multi-node NoSQL counterparts since partition tolerance is built into their foundation. That said, lately, most of the popular ones have been adding cluster support through the use of Sharding. Relational Databases are mainly based on a single node design. Relational Databases strictly comply with ACID guarantees and hence are a good choice for transactional data. There are several licensed and open-source Relational Databases out there and all of them are mature enough to be considered for production-grade applications. Relational Databases have existed for ages and they are proven in a wide variety of applications. ![]() Since data is denormalized, accessing them requires complex joins. They provide comprehensive querying layers and store data in the minimum footprint possible by denormalizing the data. Relational Databases excel at their ability to store structured data. What are Relational Databases? Image Source
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