Version-Controlled Data with Dolt (eBook, ePUB)
The Complete Guide for Developers and Engineers
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"Version-Controlled Data with Dolt" "Version-Controlled Data with Dolt" is the definitive guide to harnessing the power of data version control in modern data engineering and analytics environments. Beginning with the fundamental motivations for versioning structured data, the book comprehensively explores how auditability, reproducibility, and collaborative governance can be realized through systems purpose-built for data-drawing clear contrasts with both Git-based source control and traditional database management systems. Readers are introduced to the core concepts of commits, branches, and...
"Version-Controlled Data with Dolt" "Version-Controlled Data with Dolt" is the definitive guide to harnessing the power of data version control in modern data engineering and analytics environments. Beginning with the fundamental motivations for versioning structured data, the book comprehensively explores how auditability, reproducibility, and collaborative governance can be realized through systems purpose-built for data-drawing clear contrasts with both Git-based source control and traditional database management systems. Readers are introduced to the core concepts of commits, branches, and repositories as they apply to databases, alongside deep dives into the technical requirements for efficient versioning, collaboration models, and the complexities of managing and evolving relational schemas. The heart of the book demystifies Dolt-the world's first SQL database with Git-like version control-by illuminating its unique architecture and ecosystem. Through clear explanations of Dolt's storage internals, branching and conflict resolution strategies, and deep integration with SQL, the book equips engineers to deploy, configure, and operate Dolt in both local and distributed environments. Readers will discover best practices for repository lifecycle, authentication, monitoring, and seamless integration into data pipelines, CI/CD workflows, and multi-cloud deployments-ensuring not only performance and scalability, but also robust data security, auditing, and compliance. Beyond the technical core, this resource addresses the collaborative essence of data science in the enterprise. It provides advanced guidance on multi-user workflows, governance automation, integration with analytics tools, and real-world case studies of distributed teams succeeding with Dolt. The book closes with an exploration of emerging trends in data version control, including applications in machine learning, ecosystem innovation, extensible plugins, and the ongoing convergence of code and data. "Version-Controlled Data with Dolt" is essential reading for data engineers, architects, and technical leaders seeking resilient, transparent, and scalable data infrastructure for the next generation of data-driven collaboration.
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