Database Basics and Scalability: Covering relational design, NoSQL strategies, caching solutions, and time series data

What you'll learn

Choose between SQL, NoSQL, NewSQL, and specialized databases by understanding their distinct use cases and architectural trade-offs

Master relational databases through schema design, ACID compliance, and SQL querying for traditional enterprise applications

Understand key-value stores for high-speed caching and session management, with strategies for handling data relationships

Learn how applications with document databases like MongoDB, leverage flexible schemas and complex document queries

Learn about columnar databases like Cassandra for distributed data processing and analytics across multiple database instances

Scale applications horizontally using database sharding, replication, and distributed transaction management

Harness time series databases for IoT sensors, market data, and application monitoring with efficient data aggregation

Design systems using NewSQL databases that combine ACID compliance with horizontal scaling for global applications

Integrate Java applications with databases using JDBC and ORM frameworks while optimizing for performance

Understand graph databases for complex relationship mapping in social networks and recommendation systems

Requirements

Basic knowledge of at least one programming language

Familiarity with common system design concepts (client-server interactions, APIs)

Description

Are you preparing for an interview or working on a codebase and need a rock-solid foundation in database technologies? Look no further. Database Essentials for Backend Engineers is a comprehensive dive into the world of data storage, designed to equip you with the knowledge and confidence to make the right decisions about how and where to store your application data.We begin by exploring why data is considered the lifeblood of modern applications, showing you real-world examples of how poor database choices can cripple even the most innovative ideas. You'll learn the differences between relational and NoSQL databases—when to prioritize strong consistency, and when horizontal scalability becomes paramount. We'll cover everything from core SQL and transactional data management to powerful NoSQL paradigms like document stores, key-value pairs, columnar data, and graph databases.But it doesn't stop there. This course dives into the practicalities of scaling databases, revealing strategies like read replicas, sharding, and distributed transactions, so your system can handle massive volumes of traffic without skipping a beat. You'll see how caching mechanisms (using tools like Redis or Memcached) offload work from primary databases, while file storage (such as Amazon S3) and content delivery networks (CDNs) optimize the handling of large static assets.Moreover, we take a close look at specialized time series databases, unveiling how they streamline real-time analytics for IoT devices, financial markets, and high-velocity logging. By comparing traditional relational systems to emerging NewSQL solutions, you'll get a front-row seat to the future of global-scale data consistency—ideal for mission-critical services such as payment processing or financial transactions.Throughout the course, you'll gain hands-on exposure to Java-based integrations. We'll discuss JDBC (Java Database Connectivity) for direct queries and explore how Object-Relational Mapping (ORM) frameworks—such as Hibernate and JPA—bridge the gap between object-oriented code and relational data. This full-stack perspective ties together the conceptual and the practical, ensuring you understand not just what to do, but also how to do it.By the end of Database Essentials for Backend Engineers, you'll have a powerful toolkit that combines deep conceptual insight with real-world techniques. You'll be ready to tackle system design interviews, craft robust backend architectures, and confidently select the right database solution to deliver high performance, reliability, and scalability—no matter the size or complexity of your application.

Overview

Section 1: Introduction to Databases

Lecture 1 Introduction and goal

Lecture 2 The importance of data storage

Lecture 3 Databases in system design interviews

Lecture 4 Other data storage types

Lecture 5 History of databases

Lecture 6 Databases in backend development

Lecture 7 Audience questions

Section 2: Fundamentals of Databases

Lecture 8 Understanding database types

Lecture 9 Audience questions

Lecture 10 Database models

Lecture 11 Schemas, indexes and transactions

Section 3: Relational Databases

Lecture 12 Relational database - key ideas

Lecture 13 ACID compliance

Lecture 14 Audience questions

Lecture 15 ORM in Java

Lecture 16 Pros, cons and when to use relational databases

Lecture 17 Relational database use case study

Lecture 18 Scaling strategies with RDBMS

Section 4: NoSQL Databases

Lecture 19 Introduction to NoSQL databases

Lecture 20 Types of NoSQL databases

Lecture 21 Key-value vs document databases

Lecture 22 Audience questions

Lecture 23 Advantages and disadvantages of NoSQL databases

Lecture 24 Strategies for ACID in NoSQL DBs

Lecture 25 Audience questions

Lecture 26 Transactions in document databases

Section 5: NewSQL Databases

Lecture 27 What are NewSQL databases_

Lecture 28 Use case for NewSQL

Lecture 29 Audience questions

Section 6: Time Series Databases

Lecture 30 Time series databases

Lecture 31 How time series databases work

Lecture 32 When to choose time series database

Lecture 33 Disadvantages of time series databases

Lecture 34 Some use cases for time series databases

Section 7: Conclusion

Lecture 35 Conclusion

Aspiring Backend Engineers: Those looking to solidify their database knowledge and confidently select the right data solution in system design.,Experienced Developers: Professionals needing a refresher on modern database trends (NoSQL, caching, time series) to stay current with industry practices.,System Architects and Tech Leads: Teams or individuals designing high-traffic applications who must balance performance, scalability, and consistency.,Data Enthusiasts: Anyone keen to understand how different storage paradigms support business-critical applications, from banking systems to real-time analytics.