The commoditization of technology has reached its pinnacle with the advent of the recent paradigm of Cloud Computing. Infosys Cloud Computing blog is a platform to exchange thoughts, ideas and opinions with Infosys experts on Cloud Computing

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February 23, 2010

Accessing CouchDB for Data Storage and Retrieval

Cloud Databases are an emerging type of non relational databases which do not follow relational algebra and are generally key-value oriented systems which are used for storing internet scale data and provide easy programmatic access. Databases like Amazon SimpleDB, Cassandra from Facebook and Apache CouchDB and many others falls in the category of non relational databases and has been widely used in large consumer based applications and are quite popular.

Apache CouchDB is a document oriented, non-relational, schema less database used for storing internet scale data. Apache CouchDB provides a rich set of REST based JSON API’s to access the database to perform administrative as well as CRUD operations.

I and Rajarshi Bhose have written an article which will demonstrate how to use CouchDB for CRUD and administrative operations using Java. This article is published at Dr. Dobb’s and it can be accessed at http://www.drdobbs.com/java/223100116. To learn in detail about some of the basics of CouchDB, and various other operations that can be performed like how to create database, how to insert data into database, how to retrieve data based on “keys” and also based on “field” values, please go through the tutorial.

February 19, 2010

Accessing Hadoop DFS for Data Storage and Retrieval

Distributed File Systems (DFS) are a new type of file systems which provides some extra features over normal file systems and are used for storing and sharing files across wide area network and provide easy programmatic access.

HDFS stands for Hadoop Distributed File System and is a distributed file system designed to run on commodity hardware. Some of the features provided by Hadoop are fault tolerance, resource management, high throughput access to application data etc.

I have written a tutorial which will demonstrate how to use HDFS for basic distributed file system operations using Java. This tutorial is published at sys-con magazine and it can be accessed at http://opensource.sys-con.com/node/1287801. To learn in detail about how to use HDFS for data storage and retrieval using java, please go through the tutorial.

February 15, 2010

SaaS makes financial accounting easier

It’s been so much talked and written about technical benefits of Cloud computing. I thought of looking at it from financial accounting point of view. Comparing the traditional IT expenses with Cloud computing expenses especially SaaS model, might give a different picture of the income statement. Before I go ahead and try putting forward my interpretation, want to make a disclaimer that I am no way finance or accounting expert, this is just a plain interpretation of what I understood. Comments and suggestions are most welcome.

Continue reading "SaaS makes financial accounting easier" »

February 04, 2010

Key Value stores: Usefulness in Cloud environment

Cloud Databases are a new type of non relational (key-value oriented) databases which are used for storing internet scale data and provide easy programmatic access. Databases like Amazon SimpleDB, Apache CouchDB, Project Voldemort and many others falls in the category of non relational databases and has been widely used and are quite popular.

Features provided by some of these key value stores are: low latency, replication, scalability, distributed etc., which naturally suits them for use in cloud environment. Also the API’s provided by these key value stores are simple and easy to use.

Here are some reasons for why you would choose Key Value database platform for your application:
- The data store is cheap and integrates easily with your vendor's web services platform.
- Your data is heavily document-oriented, making it a more natural fit with the key/value data model than the relational data model.
- Your data does not need strict transactional and consistency like data related to social communities.
- Your application deal with large amount of mostly read data.
- Your foremost concern is on-demand, high-end scalability - that is, large-scale, distributed scalability, the kind that can't be achieved simply by scaling up.

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