Database Administrators Stack Exchange is a question and answer site for database professionals who wish to improve their database skills and learn from others in the community. It's 100% free, no registration required.

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

I am trying to grasp the different concepts of Database Partitioning and this is what I understood of it:

Horizontal Partitioning/Sharding: Splitting a table into different tables that will contain a subset of the rows that were in the initial table (an example that I have seen a lot if splitting a Users table by Continent, like a sub table for North America, another one for Europe, etc...). Each partition being in a different physical location (understand 'machine'). As I understood it, Horizontal Partitioning and Sharding are the exact same thing(?).

Vertical Partitioning: From what I understood ( ), there are 2 sorts of Vertical Partitioning:

  • Normalization (which consists of removing redundancies from a the database by splitting tables and linking them with a foreign key).

  • Row Splitting, here is what I don't understand, what is the difference between Normalization and Row Splitting? In what those 2 techniques differ from each other?

I have also read in this post ( ) that the difference between Horizontal Partitioning and Vertical Partitioning is that in the first you scale by adding more machines, while in the second one you scale by adding more power (CPU, RAM) to your existing machine, is that a correct definition? I thought that the core difference between those 2 techniques resides in the way you split your tables. This answer does make sense according to MongoDB's definition of Vertical Partitioning:

but it goes in contradiction with other answers or articles I have come across:

I am sorry for the load of questions but I am a bit confused as a lot of different websites that I have came across say different things.

Any help clarifying would be greatly appreciated. Any link to a clear and simple demonstration with a few tables would also be very helpful.

share|improve this question
You are mixing up Scaling and Partitioning. When talking about Hardware Scaling (Throwing more hardware at things to solve the performance problem) is when Horizontal means more machines and vertical means more CPU, RAM. So all the articles you linked to are correct when talking about the different issues. – WindRaven Mar 6 '14 at 18:12

I am not sure what you mean by "row splitting". You may mean the same thing as what's commonly called "table decomposition". This involves decomposing a table into two tables. They generally have different primary keys and often have different numbers of rows. Every column from the original table goes in one table or the other. In addition, an extra column is added in one table that serves as a foreign key reference to the other table's primary key.

What does decomposition have to do with normalization? Well normalization classically refers to adherence to the restrictions on certain well known normal forms. These normal forms are known as:

  • First Normal form
  • Second Normal form
  • Third Normal form
  • Boyce-Codd Normal form
  • Fourth normal form
  • Fifh Normal form.

Two other forms you might see mentioned are Sixth Normal form and Domain-Key Normal form

In general, when you analyze a system of tables and determine that it departs from one of these normal forms, you can obtain conformance by decomposing tables, where the particular decomposition is described in the tutorial for that normal form.

There are benefits and drawbacks to conforming to each of the normal forms. You need to learn how to normalize data and when not to.

Decomposing tables is a transformation on the logical model of the data. It's visible to anyone who looks at the table structure.

Partitioning tables usually refers to a split that occurs within a data table, but the table remains defined as just one table. The placement of certain rows on certain disks might be an example somewhat like the example you cited in your question.

This is a split that transforms the physical model of the data, but not the logical model of the data. This split will be transparent to someone who looks at the structure of the system of tables but not inside each table.

Partitioning is generally done for the sake of speed.

Normalization is generally done for the sake of eliminating certain kinds of update anomalies, in order to make managing the data correctly a little easier. It does have implications for speed, both positive and negative.

share|improve this answer

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.