In-Memory Computing

De: Ajit Singh

Narrado por: Virtual Voice

"In-Memory Computing" provides a comprehensive, practical, and accessible pathway to mastering one of the most transformative technologies in modern computer science. This book systematically demystifies the principles, architectures, and real-world applications of processing data in system RAM, moving beyond theoretical discussions to provide actionable, hands-on knowledge.


Key Features:

1. Beginner to Advanced Trajectory: The content is structured to cater to both undergraduate students new to the topic and postgraduate learners seeking in-depth knowledge.
2. Hands-On Approach: Every major concept is paired with practical examples, code snippets, and step-by-step tutorials to reinforce learning and build practical skills.
3. Real-World Case Studies: Explores how leading industries like finance, e-commerce, and telecommunications leverage In-Memory Computing to solve critical business problems.
4. Simple and Lucid Language: Complex architectural and programming concepts are explained in an easy-to-understand manner with clear diagrams and relatable analogies.
5. Comprehensive Platform Coverage: Provides a balanced overview and practical implementation guides for leading open-source IMC technologies, including In-Memory Data Grids and Databases.
6. NEP 2020 & AICTE Aligned: Emphasizes conceptual understanding, critical thinking, and experiential learning through hands-on labs and a capstone project.
7. End-to-End Capstone Project: A full final chapter is dedicated to building a complete, real-world application, integrating various concepts learned throughout the book, and includes the complete, explained source code.


To Whom This Book is For:

This book is an essential resource for a wide spectrum of learners and professionals:

1. B.Tech/B.E. Students: Undergraduate students in Computer Science, Information Technology, and related engineering disciplines studying courses on Database Management Systems, Distributed Systems, and Big Data Analytics.
2. M.Tech/M.E. Students: Postgraduate students and research scholars specializing in high-performance computing, data science, and advanced software architecture.
3. Aspiring Data Engineers and Data Scientists: Individuals looking to build a strong foundation in the technologies that power real-time data pipelines and analytics.
4. Software Developers and Architects: Professionals who want to design and build scalable, low-latency applications and microservices.
5. IT Professionals and System Administrators: Individuals responsible for deploying, managing, and optimizing high-performance data infrastructure.
6. Faculty and Academicians: Educators seeking a comprehensive, modern, and practical textbook for their curriculum that aligns with the latest educational policies.


The book's core philosophy is to simplify complex concepts and empower readers to build high-performance, data-intensive applications. It begins with the absolute fundamentals, explaining why In-Memory Computing is essential in today's data-driven landscape, and progresses logically through core architectural principles, deep dives into industry-leading platforms like Apache Ignite, Hazelcast, and Redis, and advanced topics such as stream processing and machine learning acceleration. The journey culminates in a complete capstone project where readers will build a live, working real-time fraud detection system from scratch.

Disclaimer: Earnest request from the Author.

Kindly go through the table of contents and refer kindle edition for a glance on the related contents.

Thank you for your kind consideration!