In today's data-driven world, managing large volumes of data has become a common challenge. Data-driven businesses often face the task of effectively handling and analysing such extensive datasets when real-time analysis plays a crucial role to make informed decisions. Column-oriented databases have risen in popularity as a preferred storage and analytics solution. Elisa Polystar, for instance, uses ClickHouse, a column-oriented database to provide network and service assurance solutions in their Kalix product. One of the advantages of using column-oriented databases, including ClickHouse, is the availability of compression techniques. Dictionary is an in-memory key-value structure which can be stored completely or partially in RAM and can be used in queries. This thesis conducts a series of query-based experiments to evaluate the performance of Kalix when utilising dictionary. Results show that compared to the traditional left outer join, the dictionary version performed significantly better in five queries for both query duration and memory usage. At its best, the dictionary performs 26 times faster and consumes 1526 times less memory.

Modern society is intrinsically dependent on the ability to manage data effectively. While relational databases have been the industry standard for the past quarter century, recent growth in data volumes and complexity requires novel data management solutions. These trends revitalized the interest in deductive databases and highlighted the need for column-oriented data storage. However, programming technologies for enterprise computing were designed for the relational data management model (i.e., row-oriented data storage). Therefore, developers cannot easily incorporate emerging data management solutions into enterprise systems. To address the problem above, this thesis presents Deductive Java (DJ), a system that enables enterprise programmers to use a column oriented deductive database in their Java applications. DJ does so without requiring that the programmer become proficient in deductive databases and their non-standardized, vendor-specific APIs. The design of DJ incorporates three novel features: (1) tailoring orthogonal persistence technology to the needs of a deductive database with column-oriented storage; (2) using Java interfaces as a primary mapping construct, thereby simplifying method call interception; (3) providing facilities to deploy light-weight business rules. DJ was developed in partnership with LogicBlox Inc., an Atlanta based technology startup. / Master of Science