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Difference between Row oriented and Column oriented data stores in DBMS

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Row-oriented and column-oriented data stores are two different approaches to storing and organizing data in relational database management systems (RDBMS). Row-Oriented Database work by organizing the data into rows and Column-Oriented  Databases work by organizing the data into columns.

Row-Oriented Database

In a row-oriented data store, data is stored and retrieved row-by-row, meaning that all of the attributes of a particular row are stored together in the same physical block of data. This approach is optimized for retrieving entire rows of data at a time and is typically used in traditional RDBMS systems.

In a row-oriented data store, data is organized and stored like this.

ID Name Age Department
1 John 35 IT
2 Jane 28 HR
3 Bob 42 Finance

When a query is executed in a row-oriented data store, it retrieves all the attributes of the specified row at once, including attributes that are not needed for the query. This can result in slower query performance, especially for queries that only require a subset of the attributes in a row.

Column-Oriented Database

In a column-oriented data store, data is organized and stored by columns rather than by rows. This approach is optimized for retrieving specific columns of data and is typically used in data warehousing and analytics systems.

In a column-oriented data store, data is organized and stored like this:

ID Name Age Department
1 John 35 IT 
2 Jane 28 HR
3 Bob 42 Finance

When a query is executed in a column-oriented data store, it retrieves only the specified columns of data, which can result in faster query performance. Additionally, column-oriented data stores can use compression techniques to reduce storage space and improve performance.

One potential downside of column-oriented data stores is that they may require more complex queries to retrieve entire rows of data, as the data is spread across multiple columns. However, this can often be mitigated by using specialized query languages and optimization techniques that are designed for columnar data stores.

A data store is a place for storing collections of data, such as a database, a file system, or a directory. In a Database system, they can be stored in two ways. These are as follows:

  1. Row-Oriented Data Store
  2. Column-Oriented Data Store

Difference Between Row-Oriented Database and Column-Oriented Database

Row-Oriented Database Column-Oriented Database
Data is stored and retrieved one row at a time and hence could read unnecessary data if some of the data in a row are required. In this type of data store, data are stored and retrieved in columns and hence it can only able to read only the relevant data if required.
Records in Row Oriented Data stores are easy to read and write. In this type of data store, read and write operations are slower as compared to row-oriented.
Row-oriented data stores are best suited for online transaction systems. Column-oriented stores are best suited for online analytical processing.
These are not efficient in performing operations applicable to the entire datasets and hence aggregation in row-oriented is an expensive job or operation. These are efficient in performing operations applicable to the entire dataset and hence enable aggregation over many rows and columns.
Typical compression mechanisms provide less efficient results than what we achieve from column-oriented data stores. These type of data stores basically permits high compression rates due to few distinct or unique values in columns.

The best example of a Row-oriented data store is Relational Database, which is a structured data storage and also a sophisticated query engine. It incurs a big penalty to improve performance as the data size increases. The best example of a Column-Oriented datastores is HBase Database, which is basically designed from the ground up to provide scalability and partitioning to enable efficient data structure serialization, storage, and retrieval.

Difference Between Relational Database and HBase

 
Relational Database HBase
It is basically based on a Fixed Schema. It is totally Schema-less.
It is an example of a row-oriented data store. It is an example of a column-oriented data store.
It is basically designed to store normalized data. It is basically designed to store de-normalized data.
It basically contains thin tables. It basically contains wide and sparsely oriented populated tables.
It has no built-in support for partitioning. It basically supports Automatic Partitioning.

FAQs

1. What is an example of a Row-Oriented Database?

Answer: 

Some common examples of Rows-Oriented databases are PostgreSQL and MySQL. 

2. What is an example of a Column-Oriented Database?

Answer:

Some common examples of Column-Oriented Databases are Apache Cassandra, ScyllaDB, etc.


Last Updated : 19 Jun, 2023
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