WITHDRAWN: Compression techniques for performance optimisation in columnar databases

Data has become an integral part of today’s life. Traditional relational databases are row oriented databases designed for row wise data storage and retrieval which consumes more time to return queries. Recently, Columnar databases have dominated traditional databases due to their effective read operations to and from hard disk to decrease the interval to return queries. Columnar databases are mainly designed for data warehouses where huge amount of data collected from several sources are needed to perform Business Intelligence to build decision making systems. Columnar databases have quicker query performance because the data is packed close together which decreases seek time. They support various compression techniques for quicker data access with the help of aggregation queries to filter the irrelevant data. This paper discusses about various compression techniques such as NULL Suppression, Dictionary Encoding, Run Length Encoding, Bit Vector Encoding and Lempel Ziv Encoding which are being popularly used to optimise the performance of the columnar databases. Database operations are performed on the compressed data to prove the reduction in the requirements of memory and enhancements in the performance.