If all these new DBMS technologies are so scalable, why are Oracle and DB2 still on top of TPC-C? A roadmap to end their dominance.
(This post is coauthored by Alexander Thomson and Daniel Abadi) In the last decade, database technology has arguably progressed furthest along the scalability dimension. There have been hundreds of research papers, dozens of open-source projects, and numerous startups attempting to improve the scalability of database technology. Many of these new technologies have been extremely influential---some
Distributed Programming and Data Consistency w/ Notes
This document discusses distributed programming and data consistency. It defines consistency as how systems and observers perceive the state of a system over time. Consistency has a time aspect, where expected and unexpected sequences of states can occur. Distributed systems like caching introduce inconsistencies when data is replicated across servers. The CAP theorem states that a distributed sys
Read-After-Write Consistency in Amazon S3 — Shlomo Swidler
S3 has an “eventual consistency” model, which presents certain limitations on how S3 can be used. Today, Amazon released an improvement called “read-after-write-consistency” in the EU and US-west regions (it’s there, hidden at the bottom of the blog post). Here’s an explanation of what this is, and why it’s cool. What is Eventual Consistency? Consistency is a key concept in data storage: it descri
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DataStax Python Driver - cassandra.query
http://zookeeper.apache.org/doc/trunk/zookeeperProgrammers.html
zookeeper-user - Consistency in zookeeper
http://www.cs.cmu.edu/~srini/15-446/S09/lectures/10-consistency.pdf
PowerPoint Presentation
PowerPoint Presentation
https://www.cs.princeton.edu/courses/archive/spr11/cos461/docs/lec24-strong.pdf
CAP Twelve Years Later: How the "Rules" Have Changed
