Emerging Databases for Next Generation Big Data Applications

Abstract

The rising quality of large-scale period analytics applications (real-time inventory/pricing, mobile apps that offer you suggestions, fraud detection, risk analysis, etc.) emphases the requirement for distributed knowledge management systems which will handle quick transactions and analytics simultaneously. Efficient process of transactional and analytical requests, however, need completely different optimizations and branch of knowledge selections in a system. This paper presents the wildfire system that targets Hybrid Transactional and Analytical process (HTAP). wildfire leverages the Spark system to modify large-scale processing with differing types of complicated analytical requests, and columnar processing to modify quick transactions and analytics simultaneously.