riak: All content tagged as riak in NoSQL databases and polyglot persistence

Grails 2.0 and NoSQL

About:

NoSQL databases

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Graeme Rocher:

Grails 2.0 is the first release of Grails that truly abstracts the GORM layer so that new implementations of GORM can be used. […] The MongoDB plugin is at final release candidate stage and is based on the excellent Spring Data MongoDB project which is also available in RC form. […] Grails users can look forward to more exciting NoSQL announcements in 2012 with upcoming future releases of GORM for Neo4j, Amazon SimpleDB and Cassandra in the works.

This is great news.

The very very big news would be a Grails version that doesn’t default anymore to using Hibernate for accessing a relational database.

Original title and link: Grails 2.0 and NoSQL (NoSQL database©myNoSQL)

via: http://blog.springsource.org/2011/12/15/grails-2-0-released/

NoSQL Case Study: Riak for the Danish Healthcase System

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InfoQ just published Kresten Krab Thorup presentation at GOTO conference, Riak on Drugs (and the Other Way Around), covering details about the Danish healthcare system built on top of Riak for high availability, scalability and to run off multiple data centers. Now we have both sides of the case study of building a nationwide healthcase system using Riak and Gigaspaces XAP.

Original title and link: NoSQL Case Study: Riak for the Danish Healthcase System (NoSQL database©myNoSQL)

via: http://www.infoq.com/presentations/Case-Study-Riak-on-Drugs

Building a Nationwide Healthcase System: Riak and Gigaspaces XAP

About:

Riak

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Gigaspaces XAP

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Powered by NoSQL

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This slidedeck presented by Dirk Deridder and Koen Vanderkimpen at Devoxx 2011 caught my attention not only because it describes pretty clear and succintely what the requirements of a nationwide healthcare system are, but also because I knew another similar case study which was implemented using a different solution.

Dirk Deridder and Koen Vanderkimpen, working for Smals (Belgium), have used Gigaspaces XAP, while Trifork and Basho used Riak for building a system whose architectural requirements are:

highly available
performant
scalable
flexible
secure

Architectural requirements of a Nationwide Healthcase system

Starting with slide 30, Dirk and Koen detail how Gigaspaces XAP satisfied these system requirements.

Going eXtreme for Healthcare from kovasmals

Original title and link: Building a Nationwide Healthcase System: Riak and Gigaspaces XAP (NoSQL database©myNoSQL)

Griffon and NoSQL Databases

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CouchDB

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Riak

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Redis

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Voldemort

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Neo4j

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BerkleyDB

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memcached

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Griffon

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Groovy

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Java

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Terrastore

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Db40

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Neodatis

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Andres Almiray:

The following list enumerates all NoSQL options currently supported by Griffon via plugins:

BerkeleyDB

CouchDB

Memcached

Riak

Redis

Terrastore

Voldemort

Neo4j

Db4o

Neodatis

The first 7 are Key/Value stores. Neo4j is a Graph based database. The last two are object stores. All of them support multiple datasources, data bootstrap and a Java friendly API similar to the one shown earlier.

Griffon is a Groovy-based framework for developing desktop applications. While the coolness factor of Java-based desktop apps is close to zero, having some multi-platform management utilities for these NoSQL databases might be interesting.

Original title and link: Griffon and NoSQL Databases (NoSQL database©myNoSQL)

via: http://www.jroller.com/aalmiray/entry/griffon_to_sql_or_nosql

Basho Raises $5mil for Improving Riak

About:

Riak

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Basho

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funding

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NoSQL future

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Congratulations to the Basho guys for closing an additional $5m round of funding. According to Martin Schneider “the funds will be used to make Riak an even better product. We have some seriously awesome plans for additional features, platform capabilities, cloud tools etc.”

Riak already seems like a great product to me—there’s always place for improvements though. I’d say part of the money and a tad more effort should go into making Riak a more popular product.

Details: This is the second round raised this year after the $7.5m announced in June bringing it to a total of $12.5m. The new funding comes from an inside round. Past investors in Basho have included private equity firm Georgetown Partners and Danish systems integrator Trifork AS.

Original title and link: Basho Raises $5mil for Improving Riak (NoSQL database©myNoSQL)

NoSQL: A Three-Horse Race

About:

NoSQL databases

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Couchbase

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MongoDB

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Cassandra

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HBase

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Redis

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Riak

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James Philips (Couchbase) quoted by Curt Monash:

NoSQL is simply a three-horse race between Couchbase, MongoDB, and Cassandra.

Off the top of my head I could name at least two other projects that are either having numerous deployments or are already managing huge amounts of data. And I’d bet every regular reader would figure out that I’m referring to Redis and HBase.

via: http://www.dbms2.com/2011/10/23/nosql-notes/

This article will show you how to do some Apache log analysis using Riak and MapReduce. Specifically it will give an example of how to extract URLs from Apache logs stored in Riak (the map phase) and provide a count of how many times each URL was requested (the reduce phase).

NoSQL based solutions for centralized logs analysis abound these days:

And these are just a few examples I’ve been able to pull out.

via: http://www.simonbuckle.com/2011/08/27/analyzing-apache-logs-with-riak/

It turns out you can plug all the critical Riak Stats metrics into Circonus^[1] with no effort and very little time. […] I could add all the required checks for Riak Database server under 5 minutes into Circonus!!

It is Riak to be praised here for publishing useful stats that can make an admin feel happy and in control.

Circonus: SaaS performance monitoring of both business and infrastructure metrics, in Cloud and standard environments. ↩

via: http://slowquery.blogspot.com/2011/07/monitoring-riak-using-circonus.html

Enterprises will start adopting NoSQL en masse, Rippert thinks, because the types of data they’re now dealing with require new technologies. “We are the data store for the new type of data being stored,” he explained. […]

That data is largely of the unstructured variety coming from web applications, machines and other sources that aren’t the traditional business-transaction data for which relational databases were created. Relational databases were the answer to almost everything previously, but now Rippert thinks NoSQL is “the answer to about 40 percent of business use cases today”.

A couple of follow up questions for Don Rippert^[1]:

Is your prediction of 40% market share relative to scenarios for large scale, unstructured data with high availability requirements? That would basically mean a 40% market share for just a couple of products: Cassandra, HBase, Riak, Project Voldemort, and (probably) Couchbase.
How is the rest of 60% of the market devided between the other NoSQL databases, NewSQL databases, and the traditional relational databases?
Considering the current market structure, when do you think the shift towards large scale, highly available requirements happened?
How long do you think it will take the market to remodel? What factors will accelerate this transition?

I’d really appreciate if someone could forward these questions to him. ↩

via: http://gigaom.com/cloud/why-accentures-cto-made-the-move-to-nosql-startup-ceo/

Original title and link: The Stories of the Revamped Riak Java Client and Improvements in Python Client (NoSQL database©myNoSQL)

I’m not sure how long ago I forgot about this, but I just remembered about a nice little feature when I was moving some data around on a Riak cluster. As the post title points out, this feature is streaming list keys in a bucket. […] The useful bit of this is because list_keys can be a lengthy operation, you can begin doing work on the data before you receive all of the keys.

The function is riak_client:stream_list_keys() and the post shows how to use it.

via: http://www.megarockv.com/2011/08/07/riak-erlang-stream_list_keys-example/

Google open sourced a while ago LevelDB , a C++ library that provides an ordered mapping key-value storage. LevelDB performance convinced Basho guys to experiment with adding LevelDB as a storage engine for Riak. And there’s also a benchmark comparing LevelDB with SQLite and Kyoto Cabinet.

The LevelDB project lists the following key features:

Keys and values are arbitrary byte arrays.
Data is stored sorted by key.
Callers can provide a custom comparison function to override the sort order.
The basic operations are Put(key,value), Get(key), Delete(key).
Multiple changes can be made in one atomic batch.
Users can create a transient snapshot to get a consistent view of data.
Forward and backward iteration is supported over the data.
Data is automatically compressed using the Snappy compression library.
External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions.
Detailed documentation about how to use the library is included with the source code.

You can check out also the old thread on Hacker News about LevelDB..

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