Databases Books

The SQL Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow.

With the big data boom, the rise of the Internet of Things (IoT), and the development of artificial intelligence (AI) applications, we've entered a new era of smart data. Unfortunately, not many enterprises are ready for it. Some companies are deficient in data management, while others lack standard data engineering systems. Some simply lag behind

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool - a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data

Are your data systems slowing down your AI initiatives? The potential of AI to revolutionize business is undeniable, but many organizations struggle to bridge the gap between ambitious ideas and real-world results. The cause? Traditional data architectures remain too rigid and siloed to support today's dynamic, data-intensive demands. If you're a d

Extract, transform, load (ETL) is at the center of every application of data, from business intelligence to AI. Constant shifts in the data landscape - including the implementations of lakehouse architectures and the importance of high-scale real-time data - mean that today's data practitioners must approach ETL a bit differently. This updated tech

Perform fast interactive analytics against different data sources using the Presto high-performance, distributed SQL query engine. With this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production eng

Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behav

After years of researching, coding, and talking about microservices, Edson Yanaga - Red Hat's Director of Developer Experience - hears one question frequently: how do I evolve my monolithic legacy database? In this practical report, Yanaga explains strategies for dealing with your relational database when migrating from a monolithic codebase to a m

The GraphQL API query language radically streamlines data exchanges with backend servers by representing application data as easy-to-understand graphs. You can amplify GraphQL's benefits by using graph-aware tools and data stores, like React, Apollo, and Neo4j, throughout your application. A full stack graph approach provides a consistent data mode

Discover critical considerations and best practices for improving database performance based on what has worked, and failed, across thousands of teams and use cases in the field. This open access book provides practical guidance for understanding the database-related opportunities, trade-offs, and traps you might encounter while trying to optimize