NOSQL vs SQL. Key differences and when to choose each
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Nowadays there is a rising tendency to use NoSQL databases. In this article we want to clear up the differences between both database types and on what occasions should we choose one over the other for our project. If you think you can collaborate with more characteristics or information for this article, we’ll gladly pay close attention to your commentaries.
Before proceeding, do we know the difference between NoSQL vs SQL? Simply to clear it up. The main difference between both database types lies in the fact that NoSQL databases don’t use relational models.
Relational database advantages
- Its use is more adapted and the profiles that know it are mainstream, and therefore less expensive.
- Due to the amount of time that they’ve been on the market, these tools have better support, product suites and add-ons to manage these databases.
- The atomicity of operations on the database. This means that on these databases either the entire operation is done or it’s not done at all, using the famous ‘rollback’ technique.
- The data must comply with integrity requirements both in data type and compatibility.
Disadvantages in relational databases
- The atomicity of the operations plays a crucial part in the database’s performance.
- Scalability, even though it’s usually tested in productive environments, it’s usually lower than NoSQL databases.
Advantages of a NoSQL database
- the scalability and its decentralized style. It supports distributed structures.
- They’re usually much more open and flexible as databases. They allow adapting to the needs of a project in a much easier way than entity related models.
- Changes in the schemes can be done without having to stop the database.
- Horizontal scaling: they’re capable of growing in device number, instead of having to reside in one large device.
- They can be run on low-resource devices.
- Query optimization on databases designed for large amounts of data.
Disadvantages of NoSQL databases
- Not all NoSQL databases contemplate the atomicity of instructions and the integrity of the data. They withstand what’s know as eventual consistence.
- Compatibility issues with SQL instructions. New databases use their own characteristics in the query language and they’re not yet 100% compatible with the SQL used in relational databases. Support for work query issues in a NoSQL database is more complicated.
- Lack of standardizing. There are many NoSQL databases and there is still no standard like the ones that exist in relational databases. An uncertain future is predicted for these databases.
- Cross-platform support. There are still many improvements to be made on some systems so that they can run on non-Linux operating systems.
- They usually have not-really-useful management tools or console access.
NoSQL vs SQL: When should we use which type of database?
- When the data must be consisten without leaving room for error when using a relational database. SQL.
- When our budget won’t allow large devices and must be put into lower performance devices. NoSQL.
- When the datastructures we manage are variable. NoSQL.
- For analyzing large quantities of data in read mode only. NoSQL.
- Event capture and processing. NoSQL
- Online stores with complex intelligence engines. NoSQL
At this point it’s very important to insist on the fact that even though it may look like a good time to move over to a NoSQL database, we must keep in mind before taking that decision if the characteristics of our database rather needs a NoSQL or a relational database.
We hope this article comparing both databas types (NoSQL vs SQL). Do you have information to add or comment? Any experiences with SQL or NoSQL databases? let us know, we’ll pay attention.
El equipo de redacción de Pandora FMS está formado por un conjunto de escritores y profesionales de las TI con una cosa en común: su pasión por la monitorización de sistemas informáticos.
Pandora FMS’s editorial team is made up of a group of writers and IT professionals with one thing in common: their passion for computer system monitoring.