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Spanner and F1 - Distributed Databases from Google
In this episode, we dive deep into the world of distributed SQL databases and the groundbreaking innovations that have shaped modern cloud infrastructure. We explore the concepts, architecture, and lessons behind three seminal works in the field:
1. Spanner: Google’s Globally-Distributed Database
James C. Corbett, Jeffrey Dean, Michael Epstein, Andrew Fikes, Christopher Frost, JJ Furman, Sanjay Ghemawat, Andrey Gubarev, Christopher Heiser, Peter Hochschild, Wilson Hsieh, Sebastian Kanthak, Eugene Kogan, Hongyi Li, Alexander Lloyd, Sergey Melnik, David Mwaura, David Nagle, Sean Quinlan, Rajesh Rao, Lindsay Rolig, Yasushi Saito, Michal Szymaniak, Christopher Taylor, Ruth Wang, Dale Woodford
This paper introduces Google Spanner, a highly scalable distributed SQL database that powers some of the world’s most demanding applications. We’ll discuss its unique architecture, including the use of the TrueTime API to synchronize global databases, and how it solves the challenges of consistency, availability, and partition tolerance—often referred to as the CAP Theorem.
2. Spanner, TrueTime & The CAP Theorem
Written by none other than Eric Brewer, the creator of the CAP Theorem, this paper expands on the trade-offs between consistency, availability, and partition tolerance in distributed systems. It provides an in-depth look at how Google Spanner achieves its promise of global distribution without sacrificing consistency, revolutionizing how we think about relational databases at scale.
3. F1: A Distributed SQL Database That Scales
Jeff Shute Chad Whipkey David Menestrina Radek Vingralek Eric Rollins Stephan Ellner Traian Stancescu Bart Samwel Mircea Oancea John Cieslewicz Himani Apte Ben Handy Kyle Littlefield Ian Rae*
In this paper, the engineers behind Google F1 reveal the architecture of their distributed SQL system, which powers Google’s advertising infrastructure. The F1 database combines the best of relational SQL with the scalability of NoSQL, and we’ll explore how its design enables low-latency, high-availability, and the seamless handling of massive workloads
Some or all of this content is AI generated and may contain some errors. Please use with caution.
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By EksplainIn this episode, we dive deep into the world of distributed SQL databases and the groundbreaking innovations that have shaped modern cloud infrastructure. We explore the concepts, architecture, and lessons behind three seminal works in the field:
1. Spanner: Google’s Globally-Distributed Database
James C. Corbett, Jeffrey Dean, Michael Epstein, Andrew Fikes, Christopher Frost, JJ Furman, Sanjay Ghemawat, Andrey Gubarev, Christopher Heiser, Peter Hochschild, Wilson Hsieh, Sebastian Kanthak, Eugene Kogan, Hongyi Li, Alexander Lloyd, Sergey Melnik, David Mwaura, David Nagle, Sean Quinlan, Rajesh Rao, Lindsay Rolig, Yasushi Saito, Michal Szymaniak, Christopher Taylor, Ruth Wang, Dale Woodford
This paper introduces Google Spanner, a highly scalable distributed SQL database that powers some of the world’s most demanding applications. We’ll discuss its unique architecture, including the use of the TrueTime API to synchronize global databases, and how it solves the challenges of consistency, availability, and partition tolerance—often referred to as the CAP Theorem.
2. Spanner, TrueTime & The CAP Theorem
Written by none other than Eric Brewer, the creator of the CAP Theorem, this paper expands on the trade-offs between consistency, availability, and partition tolerance in distributed systems. It provides an in-depth look at how Google Spanner achieves its promise of global distribution without sacrificing consistency, revolutionizing how we think about relational databases at scale.
3. F1: A Distributed SQL Database That Scales
Jeff Shute Chad Whipkey David Menestrina Radek Vingralek Eric Rollins Stephan Ellner Traian Stancescu Bart Samwel Mircea Oancea John Cieslewicz Himani Apte Ben Handy Kyle Littlefield Ian Rae*
In this paper, the engineers behind Google F1 reveal the architecture of their distributed SQL system, which powers Google’s advertising infrastructure. The F1 database combines the best of relational SQL with the scalability of NoSQL, and we’ll explore how its design enables low-latency, high-availability, and the seamless handling of massive workloads
Some or all of this content is AI generated and may contain some errors. Please use with caution.