Distributed Systems

When designing distributed web services, there are three properties that are commonly desired: consistency, availability, and partition tolerance. It is impossible to achieve all three. In this note, we prove this conjecture in the asynchronous network model, and then discuss solutions to this dilemma in the partially synchronous model.

In the decade since its introduction, designers and researchers have used (and sometimes abused) the CAP theorem as a reason to explore a wide variety of novel distributed systems. The NoSQL movement also has applied it as an argument against traditional databases. The CAP theorem states that any networked shared-data system can have at most two of three desirable properties: consistency (C) equivalent to having a single up-to-date copy of the data; high availability (A) of that data (for updates); and tolerance to network partitions (P)....

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data....

When Satoshi Nakamoto first set the Bitcoin blockchain into motion in January 2009, he was simultaneously introducing two radical and untested concepts. The first is the “bitcoin”, a decentralized peer-to-peer online currency that maintains a value without any backing, intrinsic value or central issuer. So far, the “bitcoin” as a currency unit has taken up the bulk of the pu blic attention, both in terms of the political aspects of a currency without a central bank and its extreme upward and downward volatility in price....

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