Data Storage and Querying: Databases to Vector Search

Data is the backbone of modern software, but how does it actually live on a disk or in memory? Understanding how storage systems organize and retrieve information is essential for building efficient, scalable applications. This course guides you through the entire landscape of data architecture, from raw physical storage to advanced database queries. In this course, you will learn the core concepts that govern data systems and gain hands-on comprehension of modern retrieval techniques. You will explore how different storage models solve unique engineering challenges and how new AI technologies utilize specialized databases. What you'll learn: - Understand the fundamental differences between file, block, and object storage systems. - Explore how database engines structure data in memory and on disk for rapid access. - Write graph queries using the Cypher language to navigate relationships in Neo4j. - Apply vector similarity search concepts used to power modern generative AI and search engines. - Compare relational, non-relational, and specialized database models to choose the right tool for your project. You will start with core terminology and physical storage mechanics before moving into database architectures, graph databases, and modern vector storage solutions. Through clear written explanations and practical query exercises, you will build a solid foundation in data retrieval. This course is designed for aspiring developers, data enthusiasts, and technical beginners with no prior database experience. Start reading today to unlock the mysteries of how data is stored, managed, and queried.