Paper: Scalable Eventually Consistent Counters over Unreliable Networks - High Scalability -
« Stuff The Internet Says On Scalability For March 14th, 2014 | Main | Douglas Adams - 3 Rules that Describe Our Reactions to Technologies » Counting at scale in a distributed environment is surprisingly hard. And it's a subject we've covered before in various ways: Big Data Counting: How to count a billion distinct objects using only 1.5KB of Memory, How to update video views count effectively?,
MDCC: Multi-Data Center Consistency
A new commit protocol and transaction programming model for efficiently achieving strong consistency in databases across data centers. With the emergence of cloud services, distributed databases have benefited from many of the advantages of deploying on a clusters of machines. However, entire data centers of machines can fail. Here are just a few recent data center failures, and one even losing cu
SNA Projects Blog : Tech Talk: Michael Deerkoski (Flickr) — “Continuous Deployment at Flickr”
LinkedIn operates the world’s largest professional network with more than 645 million members in over 200 countries and territories. This team builds distributed systems that collect, manage and analyze this digital representation of the world's economy, while our AI experts, data scientists and researchers conduct applied research that fuel LinkedIn’s data-driven products and provide insights tha
Spanner: Google's Globally-Distributed Database
Spanner is Google's scalable, multi-version, globally-distributed, and synchronously-replicated database. It is the first system to distribute data at global scale and support externally-consistent distributed transactions. This paper describes how Spanner is structured, its feature set, the rationale underlying various design decisions, and a novel time API that exposes clock uncertainty. This AP
Eventual consistency with MySQL
tl;dr : New 'automatic' optimistic conflict detection functions available giving the best of both optimistic and pessimistic replication on the same data MySQL replication supports a number of topologies, and one of the most interesting is an active-active, or master-master topology, where two or more Servers accept read and write traffic, with asynchronous replication between them. This topology
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HBase Read High Availability Using Timeline Consistent Region Replicas
http://arxiv.org/pdf/1307.3207v1.pdf