denormalization

You Can Still Use RDBMS over NoSQL {1}

by Hieu H
NoSQL is definitely the buzz in the database world. With such open source packages such as MongoDB and FoundationDB, it makes us NoSQL as accessible as it can get. There are still benefits to using relational databases, such as the ability to use normalization, shared data, and maturity. Some instances in which using a relational database over NoSQL are advantageous include when you’re building smaller databases that are still going to change over time, when there is so much duplicate data that you have to normalize, and when there is no cost advantage to moving away from already proven technology. read more...

Denormalization: Intermediate Step {5}

by Jasmine C
The article I read about is very informative.  A quick synopsis of the article is that it discusses a lot of information regarding the techniques of denoralization and the pros and cons of normalization vs denoralization.  Today, normalization is the way to designing a relational database.  However, the biggest disadvantage of normalization is that system performance is very poor.  With normalization, data is organized so that there is minimal updating and data is easily accessible.   At the moment, denormalization techniques do not have concrete guidelines to guide the process.   However, denormalization shows a positive effect on a databases’s performance.   It has been proposed that denormalization be used, in addition to normalization, to play as a middle step to help with system performance .  This article describes three approaches that are used to review the donormalization strategies.  Each of the approaches shows how denormalization positively affects databases. read more...

Normalization vs Denormalization {1}

by Antonio M
This article talks about the differences between Normalization and Denormalization.
The author also lists the the pros and cons of using each technique. Some of the
advantages of Normalized data is that when data needs to be updated in a table
they can be updated much faster because there will not be any duplicated data.
This is good because when using an INSERT statement the data can be inserted into
one location this is also similar when you would use a SELECT statement when getting
data from a single table. One of the issues with normalization is when you join
tables that have been normalized indexing strategies will not work well for these
tables because data can be spread out among other tables. As for the advantages
for denormalization is mostly beneficial when there is a big need to read-load
data from a database. The reason being is that majority of the data needed are
present in the table that is being selected so there would be no need to join
tables since this can be time consuming. Although there will be duplicate data
in a denormalized table and this can be complex when updating data. The author
says that the best way to decide when to either normalize or denormalize a database
is to have a mixture of both and just depends on the need of the database, if it
is read more or updated more. One suggestion the other had mentioned is the use
of triggers when a table has been denormalized, that way when there is ever a need
to update information in a denormalized table instead of updating duplicate data
it can reference the table where that duplicate data is coming from and save time
rather than going through each row of a database and updating it one by one. read more...