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Hackery :: Exploring Riak
Been playing with Riak recently, which is one of the modern dynamo-derived nosql databases (the other main ones being Cassandra and Voldemort). We're evaluating it for use as a really large brackup datastore, the primary attraction being the near linear scalability available by adding (relatively cheap) new nodes to the cluster, and decent availability options in the face of node failures. I've built riak packages for RHEL/CentOS 5, available at my repository , and added support for a riak 'target' to the latest version (1.10) of brackup (packages also available at my repo). The first thing to figure out is the maximum number of nodes you expect your riak cluster to get to.Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison :: KKovacs
(Yes it's a long title, since people kept asking me to write about this and that too :) I do when it has a point.) While SQL databases are insanely useful tools, their monopoly in the last decades is coming to an end. And it's just time: I can't even count the things that were forced into relational databases, but never really fitted them. (That being said, relational databases will always be the best for the stuff that has relations .)
Blog of Data » Blog Archive » Benchmarking Riak for the Mozilla Test Pilot Project
Introduction: Using A Riak Cluster for the Mozilla Test Pilot Project As part of integrating Test Pilot into the Firefox 4.0 beta , we needed a production-worthy back-end for storing the experiment results and performing analysis on them. As discussed in the previous blog post, Riak and Cassandra and Hbase, oh my!
Latest News: Getting Started With Riak & Python
Riak is one of a handful of non-relational datastores that has experienced some exposure lately, and with good reason. It's written in Erlang, is Dynamo -inspired and, while technically is a key-value store, functions very well in our experience as a document store (meaning you can store complex data as the value). Reading through the overview is highly recommended. It's also extremely predictable in production, handles node failures well and (here's the really interesting bit) demonstrates linear performance as you add nodes (see these benchmarks ). This is impressive because many distributed systems, especially in the NoSQL space, don't behave like this. Like many other NoSQL options, it uses MapReduce for many types of queries (which you can write in either Javascript for ad hoc queries or Erlang for repetitious, speedy queries).
Today I get back into my post series about the Google Technology Stack , with a more detailed look at distributed dictionaries, AKA distributed key-value stores, AKA distributed hash tables . What we’d like to do is store a dictionary of key-value pairs across a cluster of computers, preferably in a way that makes it easy to manipulate the dictionary without having to think about the details of the cluster. The reason we’re interested in distributed dictionaries is because they’re used as input and output to the MapReduce framework for distributed computing. Of course, that’s not the only reason distributed dictionaries are interesting – they’re useful for many other purposes (e.g., distributed caching). But for the purposes of this post, we’ll imagine our distributed dictionaries are being used as the input and output from a MapReduce job.
Consistent hashing
October 31, 2010 - by badnima Recently Basho and Joyent entered into a comprehensive partnership to deliver Riak Smartmachines to Joyent customers. We had been experimenting with Riak since early in 2010 and were eager to benchmark its performance on Joyent and ultimately offer a robust NO-SQL solution to our customers.
Riak SmartMachine Benchmark: The Technical Details
It has been a long time coming, but the first post is finally here! This is the first in a series of post, as promised a while ago , covering off web development using Erlang . This post is the ubiquitous “get up and running” post, which aims to get your environment set up so that you can dive in to development. The next post will detail how to handle a basic end-to-end web request. First up, a few things we need to be aware of before we begin:
Webmachine, ErlyDTL and Riak – Part 1 | OJ's rants
Exploring Riak with Clojure
Riak is an open source distributed datastore optimized for internet-scale operations. Riak provides horizontally scalable key-value storage and a distributed JavaScript map-reduce query layer. These features make Riak an interesting candidate for backing large-scale applications.The awesome dudes at Basho released Riak 0.13 and with it their first version of Riak Search yesterday. This is all kinds of exciting, and I'll tell you why. Riak Search is (way down below) based on Lucene, both the library and the query interface.
Why Riak Search Matters...
travisswicegood.com
I talk with a lot of people about NoSQL. I’ve been following it pretty closely for about 3 years now. One of the things I often tell people who are trying to wrap their heads around the concepts of NoSQL and what all of the data stores mean is to go search for Justin Sheehy and his NoSQL East Talk .riak-js
I found riak-js today. It’s a JavaScript driver for connecting to Riak datastores. I hadn’t actually heard of Riak, so I’ve been reading up on it: Riak is heavily influenced by Dr. Eric Brewer’s CAP Theorem and Amazon’s Dynamo paper.Latest riak news on coder.io
coder.io is.. no more. It was a news and article aggregation site for developers but never took off and despite being semi-abandoned for the last two years, it continued to run and attract about 8,000 visitors a month. Thanks to you all!How would you implement a key-value storage system if you were starting from scratch? The approach Basho settled on with Bitcask , their new backend for Riak, is an interesting combination of using RAM to store a hash map of file pointers to values and a log-structured file system for efficient writes. In this excellent Changelog interview , some folks from Basho describe Bitcask in more detail.
Riak's Bitcask - A Log-Structured Hash Table for Fast Key/Value Data
Saturday, October 02, 2010 - 03:30 PM - 04:00 PM Abstract: Storing big data reliably is hard. Searching that data is just as hard. Basho Technologies, the company behind Riak KV and Riak Search, focuses on solving these two problems.
Riak Core: Building Distributed Applications Without Shared State | Commercial Users of Functional Programming
So I stumbled upon Rob Vesse’s tweet the other day, where he said he was about to use MongoDB for storing RDF. A week earlier I watched a nice video about links and link walking in Riak, “a Dynamo-inspired key/value store that scales predictably and easily” (see also the Wiki doc ). Now, I was wondering what it takes to store an RDF graph in Riak using Link headers . Let me say that it was very easy to install Riak and to get started with the HTTP interface . The main issue then was how to map the RDF graph into Riak buckets, objects and keys. Here is what I came up so far – I use a RDF resource-level approach with a special object key that I called :id , which is the RDF resource URI or the bNode.