Columnar Databases: Which Data needs are best suited to them?

A column database is a relational database architecture where data is arranged in columns as opposed to rows, as with traditional relational database architecture. This architecture is essential for the creation of database management systems as it forms the foundation of the data management architecture that is used. Columnar databases are a recent introduction in the world of computing that provide a new way of organizing large data sets in preparation of retrieval, storage, processing and other related tasks.

What is different about column database architecture?

The main difference between columnar databases and the traditional databases is the arrangement of the data. In the traditional systems, rows were used to collate the data that are being stored. This meant that the data was arranged in rows depending on the nature of the data. The different segments of the data that are being stored will be sorted via the use of different titles on the row file of the data. This means that a single set of data that are related to say, for example, a single customer will be sorted into different rows but the same column.

In columnar database architecture, the data that are being stored is sorted into different columns instead of rows. This means that the columns provide the distinction between the differences in data, for example, the phone numbers and home addresses are placed in different columns. The rows are used to delineate the data as per the specific source of said data. It is, therefore, quite evident that the main difference in the physical layout of these two data architectures is the arrangement. This and column database is a reversal of the traditional relational database layout.

What is so significant about this change?

This new format for relational database architecture is proving to be a treasure trove of useful features for use in the modern data needs of companies. The columnar database is easier to manage and it provides a better format for creating powerful search query languages for use in real time data management needs. Companies are, therefore, able to use these databases to create more powerful and responsive systems for online data analysis, storage, retrieval, and processing. Furthermore, these databases are much faster and column database is much better at handling large sets of relational data than traditional databases. It has, therefore, become the go-to data format for use where the data that are being handled is in exceedingly large quantities.