NoSQL Week in Review #7
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last week was thanksgiving here in the states, we hope everyone had a good time even if you don't celebrate it! we at dzone had a great time, but this week it seems like everybody's getting sick. oh well, it happens. here's your nosql news!
new releases this week:
today we are releasing updated versions of most of the officially supported mongodb drivers with new error checking and reporting defaults. see below for more information on these changes, and check your driver docs for specifics.
over the past several years, it’s become evident that mongodb’s previous default behavior (where write messages did not wait for a return code from the server by default) wasn’t intuitive and has caused confusion for mongodb users. we want to rectify that with minimal disruption to the mongodb apps already in production.
this is the newest redis version replacing redis 2.4. redis 2.6 features support for lua scripting , milliseconds precision expires, improved memory usage, unlimited number of clients, improved aof generation, better performance, a number of new commands and features. for the complete list of new features, and the list of fixes contained in each 2.6 release, please check the release notes .
this week's top 10 nosql links:
along with kruskal’s minimum spanning tree algorithm, there’s another general algorithm that solves the problem. the algorithm of prim.
this article shows how to use the mongodb spatial feature in combination with spring and a web rest service.
this post is about my first foray into the graph database world. i chose as my first victim/offering neo4j. i'll likely end up writing more than a few articles about this particular database, but, i thought i'd start with the basics.
as of late, i've become fascinated with the whole nosql paradigm. having spent most of my professional career dealing with rdbmses, i was curious as to how the whole big data notion fit into things.
5. loading json data in couchbase
this blog describes the cbdocloader tool in more detail. it saved me a ton of time by allowing me to import an entire vancouver tree dataset that i was playing with.
one obvious application of a graph databases such as hypergraphdb is the implementation of artificial neural networks (nns). in this post, i will show one such implementation based on the practical and informative book "programming collective intelligence" by toby segaran.
why combine these two different things? so we can prepare our dataset with hadoop and import it into neo4j, the graph database, to be able to query and visualize the data.
this post demonstrates how to set up the cluster on amazon ec2 (a popular cloud service provider) with titan and faunus graph technologies.
hypergraphdb was announced as a graph database. but there's been criticism in the past that it was actually more of an oo database than a graph database, so why not call it that?
i’m really happy to share that, in a coordinated effort, all official mongodb drivers are changing their defaults to return a response from writes today.
december 11, 2012 at 10am pst
the terminology surrounding nosql and bigdata are confusing to it professionals trying to select the right storage for the right problem. andrew oliver of os integrators will explore the technical reasons you might select one of these nosql databases, the different types of databases available, their correct use and 'quintessential' use cases for them. dipti borkar of couchbase will dive deeper into document databases and the features of couchbase server 2.0
in this webinar you'll learn:
- why you can't just use rdbms for everything, and why you need different types of databases
- when it’s better to use a document database and when it’s not
- the differences between key-value store databases, document databases and graph databases
- a deeper dive into document databases and couchbase server 2.0
thanks for reading! see you soon!
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