Columnar databases store data by column rather than by row. This allows for faster analytical queries on large datasets by minimizing the movement of read/write heads across disk drives. Columnar databases are well-suited for data warehousing and business intelligence tasks that require aggregating large amounts of data, while row-oriented databases are better for transactional applications that involve frequent updates to small subsets of data.

1. Columnar Databases

2. What is Columnar Database?
• stores data in columns rather than the rows
• read data more efficiently and return queries with greater speed
• called the future of business intelligence (BI) because it allows for instant
analytical queries that enterprises depend on for business decisions
• used in data warehouses where businesses send massive amounts of data
from multiple sources for BI analysis

3. What is Columnar Database?
Row Oriented
Column Oriented

4. Why are columnar databases faster for data
warehouses?
• Storage systems have to pull data from physical disk drives, which store
information magnetically on spinning platters using read/write heads that
move around to find the data that users request.
• The less the heads have to move, the faster the drive performs.
• If data is kept closer together, minimizing seek time, systems can deliver
that data faster.

5. Columnar Database Versus Row Based
Database
fields for each
record are
sequentially
stored i a
long row

6. Columnar Database Versus Relational
Database
relational database
 ideal for transactional applications
columnar database
preferred for analytical applications
designed for data warehousing and big data processing
drastically reduces the overall disk I/O requirements

7. Column Oriented

8. Pros and Cons of Columnar Database
• To summarize, columnar databases are good for:
• Queries that involve only a few columns
• Aggregation queries against vast amounts of data
• Column-wise compression
• But are not so good at:
• Incremental data loading
• Online Transaction Processing (OLTP) usage
• Queries against only a few rows