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C# - What NoSQL solutions are out there for .NET. Michael C. Kennedy's Weblog - MongoDB vs. SQL Server 2008 Performance Showdown. This article is a follow up one I wrote last week entitled “The NoSQL Movement, LINQ, and MongoDB – Oh My!”. In that article I introduced the NoSQL movement, MongoDB, and showed you how to program against it in .NET using LINQ and NoRM. You can also watch my conference presentation at MongoDB Seattle 2011 or this DevelopMentor webcast. I highlighted two cornerstone reasons why you might ditch your SQL Server for the NoSQL world of MongoDB.

Those were 1. Ease-of-use and deployment 2. Performance For ease-of-use, you’ll want to read the original article. This article is about the performance argument for MongoDB over SQL Server (or MySql or Oracle). “A potentially controversial graph showing MongoDB performing 100 times better than SQL Server” We’ll see source code, downloadable and executable examples and you can verify all of this for yourselves.

“Data is money” Let’s imagine you’re creating a website that is for-pay and data intensive. One more story before we see the statistics. MongoDB: Database - MongoDB vs. Cassandra. HBase vs Cassandra: why we moved « Dominic Williams. My team is currently working on a brand new product – the forthcoming MMO www.FightMyMonster.com. This has given us the luxury of building against a NOSQL database, which means we can put the horrors of MySQL sharding and expensive scalability behind us. Recently a few people have been asking why we seem to have changed our preference from HBase to Cassandra.

I can confirm the change is true and that we have in fact almost completed porting our code to Cassandra, and here I will seek to provide an explanation. For those that are new to NOSQL, in a following post I will write about why I think we will see a seismic shift from SQL to NOSQL over the coming years, which will be just as important as the move to cloud computing. That post will also seek to explain why I think NOSQL might be the right choice for your company. But for now I will simply relay the reasons why we have chosen Cassandra as our NOSQL solution. Did Cassandra’s bloodline foretell the future?

Like this: Like Loading... Construction. In the past month or two, fully 8 of my colleagues from the Google Wave project have resigned from the company. This is no strange coincidence given that annual bonuses for 2010 were paid out at the end of Q1 2011. However, it does give one pause to think about so many people from the same project (including myself) counting down the bonus clock. For my part I really enjoyed my time at Google--it is the best job I've ever had, by a long way. Everything you hear about is true: the friendly atmosphere, the freedom to pursue innovative ideas and projects, capricious indulgence of engineers, and the noble sense of purpose to change the world for the better with nary a thought given to profits or costs.

So why did we all quit? Productivity Looking back, I did achieve a lot at Google--on Wave I helped design the search and indexing pipeline which was the single best-scaling component in the entire system, supporting over 3 million users at one point. Yet, I never once felt productive. Speed. Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison :: KKovacs. 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.) But, the differences between NoSQL databases are much bigger than ever was between one SQL database and another. This means that it is a bigger responsibility on software architects to choose the appropriate one for a project right at the beginning. In this light, here is a comparison of Open Source NOSQL databases: The most popular ones # Redis # Best used: For rapidly changing data with a foreseeable database size (should fit mostly in memory). For example: To store real-time stock prices. Cassandra # Best used: When you need to store data so huge that it doesn't fit on server, but still want a friendly familiar interface to it.

MongoDB # ElasticSearch # CouchDB # Accumulo #