This book, "Concept of Time-Series Database," is born out of a clear necessity. As educator and professional, I observed a significant gap in academic literature. While countless resources exist for relational and NoSQL databases, a dedicated, student-focused guide that navigates the landscape of time-series databases from foundational principles to advanced, practical implementation was conspicuously absent. This text is my endeavor to fill that void, providing a comprehensive roadmap for the next generation of engineers, developers, and data scientists.
and applicable.
Who is this book for?
1. B.Tech and M.Tech Students in Computer Science, IT, and related engineering disciplines.
2. Aspiring Data Engineers and Database Administrators who want to specialize in time-series systems.
3. Software Developers and DevOps Engineers building monitoring, IoT, or real-time analytical systems.
4. Data Analysts and Scientists who need to work with time-stamped datasets.
5. University Professors and Educators looking for a structured, NEP 2020-compliant textbook for their courses.
What you will learn from this book:
1. Master the fundamental concepts that define time-series data.
2. Understand the architectural differences between time-series and traditional databases.
3. Learn proven techniques for designing and modeling efficient time-series schemas.
4. Gain hands-on experience with industry-leading TSDBs like InfluxDB and TimescaleDB.
5. Write powerful queries to aggregate, analyze, and transform time-series data.
6. Build interactive and insightful dashboards using tools like Grafana.
7. Explore real-world case studies from FinTech, IoT, and DevOps.
8. Build a complete, end-to-end capstone project from scratch.
Key Features:
1. Beginner to Advanced Progression: The content is carefully curated to provide a smooth learning curve, starting with basic definitions and concluding with advanced topics and a live project, making it suitable for both undergraduate and postgraduate learners.
2. Hands-On and Practical: Theory is immediately followed by practice. The book is packed with code samples, step-by-step labs, and configuration guides to ensure you learn by doing.
3. Real-World Case Studies: Dedicated chapters explore how time-series databases are used to solve critical problems at companies in various industries, providing context and motivation.
4. Clear and Simple Language: Complex technical concepts are explained in the simplest and most relevant manner possible, using analogies and practical examples to aid comprehension.
5. Focus on Modern Technologies: The book provides deep dives into popular and marketable technologies like InfluxDB, TimescaleDB, and Grafana, ensuring the skills you learn are current and in-demand.
6. Complete Capstone Project: The final chapter guides you through building a fully functional IoT monitoring system, integrating all the concepts learned throughout the book into a single, impressive portfolio piece.
