System Design Topics Roadmap
Day 1: CAP Theorem
CAP theorem, also known as Brewer's theorem, is a fundamental principle in distributed systems that states that it is impossible for a distributed data system to simultaneously guarantee all of the following three properties:
Consistency: Every read receives the most recent write or an error.
Availability: Every request receives a response, but it might not be the most recent write.
Partition tolerance: The system continues to operate despite network failures.
According to CAP theorem, a distributed system can only provide at most two out of these three properties at any given time. This theorem has significant implications for designing and understanding the trade-offs in distributed systems, particularly in terms of consistency and availability under network partitions.
https://www.bmc.com/blogs/cap-theorem
https://www.ibm.com/topics/cap-theorem
Consistency: Every read receives the most recent write or an error.
Availability: Every request receives a response, but it might not be the most recent write.
Partition tolerance: The system continues to operate despite network failures.
According to CAP theorem, a distributed system can only provide at most two out of these three properties at any given time. This theorem has significant implications for designing and understanding the trade-offs in distributed systems, particularly in terms of consistency and availability under network partitions.
https://www.bmc.com/blogs/cap-theorem
https://www.ibm.com/topics/cap-theorem
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Day 1 - CAP Theorem
CAP theorem, also known as Brewer's theorem, is a fundamental principle in distributed systems that states that it is impossible for a distributed data system to simultaneously guarantee all of the following three properties:
Consistency: Every read receives the most recent write or an error.
Availability: Every request receives a response, but it might not be the most recent write.
Partition tolerance: The system continues to operate despite network failures.
According to CAP theorem, a distributed system can only provide at most two out of these three properties at any given time. This theorem has significant implications for designing and understanding the trade-offs in distributed systems, particularly in terms of consistency and availability under network partitions.
https://www.bmc.com/blogs/cap-theorem
https://www.ibm.com/topics/cap-theorem
Consistency: Every read receives the most recent write or an error.
Availability: Every request receives a response, but it might not be the most recent write.
Partition tolerance: The system continues to operate despite network failures.
According to CAP theorem, a distributed system can only provide at most two out of these three properties at any given time. This theorem has significant implications for designing and understanding the trade-offs in distributed systems, particularly in terms of consistency and availability under network partitions.
https://www.bmc.com/blogs/cap-theorem
https://www.ibm.com/topics/cap-theorem
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