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The Computer Science behind a modern distributed data store

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The Computer Science behind a modern distributed data store
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The science it takes to build a multi-threaded, clustered and highly performant database
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94
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CC Attribution 4.0 International:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Abstract
The science it takes to build a multi-threaded, clustered and highly performant database What we see in the modern data store world is a race between different approaches to achieve a distributed and resilient storage of data. Most applications need a stateful layer which holds the data. There are at least three necessary ingredients which are everything else than trivial to combine and of course even more challenging when heading for an acceptable performance. Over the past years there has been significant progress in respect in both the science and practical implementations of such data stores. In his talk the audience is introduced to some of the needed ingredients, address the difficulties of their interplay and show four modern approaches of distributed open-source data stores. Topics are: – Challenges in developing a distributed, resilient data store – Consensus, distributed transactions, distributed query optimization and execution – The inner workings of ArangoDB, Cassandra, Cockroach and RethinkDB The talk will touch complex and difficult computer science, but will at the same time be accessible to and enjoyable by a wide range of developers.