The journey to NoSQL. The NoSQL movement. In a conversation last year, Justin Sheehy, CTO of Basho, described NoSQL as a movement, rather than a technology.
This description immediately felt right; I’ve never been comfortable talking about NoSQL, which when taken literally, extends from the minimalist Berkeley DB (commercialized as Sleepycat, now owned by Oracle) to the big iron HBase, with detours into software as fundamentally different as Neo4J (a graph database) and FluidDB (which defies description). But what does it mean to say that NoSQL is a movement rather than a technology? We certainly don’t see picketers outside Oracle’s headquarters. Justin said succinctly that NoSQL is a movement for choice in database architecture. There is no single overarching technical theme; a single technology would belie the principles of the movement. Think of the last 15 years of software development. Since the ’80s, the dominant back end of business systems has been a relational database, whether Oracle, SQL Server or DB2.
The sacred cows.
Notes on MongoDB, GridFS, sharding and deploying in the cloud. We‘ve been using MongoDB in production for about six months with YippieMove.
It’s been an interesting experience and we’ve learned a lot. Contrary to many MongoDB deployments, we primarily use it for storing files in GridFS. We switched over to MongoDB after searching for a good distributed file system for years. Prior to MongoDB we used a regular NFS share, sitting on top of a HAST-device. That worked great, but it didn’t allow us to scale horizontally the way a distributed file system allows. Enter MongoDB. In the post, I will go over some of the things we’ve learned when using MongoDB. Running MongoDB in the Cloud.
Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison. (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.) But, the differences between NoSQL databases are much bigger than ever was between one SQL database and another. Why are column oriented databases so much faster than row oriented databases? - Terence Siganakis. I have been playing around with Hybrid Word Aligned Bitmaps for a few weeks now, and they turn out to be a rather remarkable data structure.
I believe that they are utilized extensively in modern column oriented databases such as Vertica and MonetDB. Essentially HWABs are a data structure that allows you to represent a sparse bitmap (series of 0's and 1's) really efficiently in memory. The key trick here is the use of run length encoding to compress the bitmap into fewer bits while still allowing for lightening fast operations. They key operation from my perspective is the "AND" operation. Google - MoreSQL Is Real. The State of NoSQL in 2012 - Practical Cloud Computing. Preamble Ramble If you’ve been working in the online (e.g. internet) space over the past 3 years, you are no stranger to terms like “the cloud” and “NoSQL”.
In 2007, Amazon published a paper on Dynamo. The paper detailed how Dynamo, employing a collection of techniques to solve several problems in fault-tolerance, provided a resilient solution to the on-line shopping cart problem. A few years go by while engineers at AWS toil in relative obscurity at standing up their public cloud. It’s December 2008 and I am a member of Netflix’s Software Infrastructure team. Huh? A month into the investigation, we start wondering about our Oracle database. Fast forward to the end of 2011: the past 3 years have been an amazing ride. Fast forward to today: I’ve completed my first month at LinkedIn.
NoSQL and Cloud Computing to the rescue? NosqlDistilled. By Pramod J.
Sadalage and Martin Fowler. PolyglotPersistence. Database · noSQL · application architecture tags: In 2006, my colleague Neal Ford coined the term Polyglot Programming, to express the idea that applications should be written in a mix of languages to take advantage of the fact that different languages are suitable for tackling different problems.
Complex applications combine different types of problems, so picking the right language for the job may be more productive than trying to fit all aspects into a single language. Over the last few years there's been an explosion of interest in new languages, particularly functional languages, and I'm often tempted to spend some time delving into Clojure, Scala, Erlang, or the like. But my time is limited and I'm giving a higher priority to another, more significant shift, that of the DatabaseThaw.
This polyglot affect will be apparent even within a single application[2]. AggregateOrientedDatabase. Database · noSQL tags: One of the first topics to spring to mind as we worked on Nosql Distilled was that NoSQL databases use different data models than the relational model.
Most sources I've looked at mention at least four groups of data model: key-value, document, column-family, and graph. Amazon DynamoDB – a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Today is a very exciting day as we release Amazon DynamoDB, a fast, highly reliable and cost-effective NoSQL database service designed for internet scale applications.
DynamoDB is the result of 15 years of learning in the areas of large scale non-relational databases and cloud services. Several years ago we published a paper on the details of Amazon’s Dynamo technology, which was one of the first non-relational databases developed at Amazon. The original Dynamo design was based on a core set of strong distributed systems principles resulting in an ultra-scalable and highly reliable database system.
Amazon DynamoDB, which is a new service, continues to build on these principles, and also builds on our years of experience with running non-relational databases and cloud services, such as Amazon SimpleDB and Amazon S3, at scale. It is very gratifying to see all of our learning and experience become available to our customers in the form of an easy-to-use managed service.