Consequently, this store type is used in case cells’ content is not important for analysis – this means that there is no connection between the cells within the database.
Key-value storage didn’t manage to replace relational database, still it is widely used as object’s cache, because cached objects of different users aren’t connected as well; the more important aspects are cache access speed and opportunity to change system’s scale.
Still, relational DBs occupy the top position on the market giving odds to No SQL solutions.
The best No SQL solutions cope with specific tasks and are usually created by leading IT companies, such as Google, Amazon, Microsoft and Apache to deal with their needs.For example, Google App Engine Data Store can be used only with Google web-services, SQL Data Services is a part of Microsoft Azure platform and Simple DB is a part of Amazon Web Services.This concept revealed the need of a completely new database model that would be aimed at access speed and scalability.The solution that would be simplier than relational database and at the same time not less effective in completing such tasks as constructing a cloud storage, where user primarily values access speed and big data volume.That is why this very storage type is so attractive for companies that provide cloud hosting services.
On the other hand, key-value storage simplicity makes the majority of ordinary operations with storage values complicated or even impossible.
And “a completely new system, a fresh idea that will change everything” – one could usually hear something like that from No SQL promoters.
However, in reality no global breakthrough happened.
Moreover, the key problem isn’t the narrow specialization of No SQL, but the range of flaws.
They might be minor for IT corporations, but rather crucial for the majority of ordinary companies.
For instance, it doesn’t ask for any database construction schemes and there is no connection between values.