Orange Slate

A document-oriented database is a designed for storing, retrieving, and managing document-oriented, or semi structured data. Document-oriented databases are one of the main categories of NoSQL databases. The central concept of a document-oriented database is the notion of a Document. While each document-oriented database implementation differs on the details of this definition, in general, they all assume documents encapsulate and encode data (or information) in some standard format(s) (or encoding(s)). Encodings in use include XML, YAML, JSON and BSON, as well as binary forms like PDF and Microsoft Office documents (MS Word, Excel, and so on).

• MongoDB:  MongoDB is a collection-oriented, schema-free document database. Data is grouped into sets that are called ‘collections’. Each collection has a unique name in the database, and can contain an unlimited number of documents. Collections are analogous to tables in a RDBMS, except that they don’t have any defined schema.

It store data (which is in BASON – “Binary Serialized dOcument Notation” format) that is a structured collection of key-value pairs, where keys are strings, and values are any of a rich set of data types, including arrays and documents.

Home: http://www.mongodb.org/
Quick Start: http://www.mongodb.org/display/DOCS/Quickstart
Download: http://www.mongodb.org/downloads

• CouchDB:  CouchDB is a document database server, accessible via a RESTful JSON API.  It is Ad-hoc and schema-free with a flat address space. Its Query-able and index-able, featuring a table oriented reporting engine that uses JavaScript as a query language. A CouchDB document is an object that consists of named fields. Field values may be strings, numbers, dates, or even ordered lists and associative maps.

Home: http://couchdb.apache.org/
Quick Start: http://couchdb.apache.org/docs/intro.html
Download: http://couchdb.apache.org/downloads.html

• Terrastore: Terrastore is a modern document store which provides advanced scalability and elasticity features without sacrificing consistency. It is based on Terracotta, so it relies on an industry-proven, fast clustering technology.

Home: http://code.google.com/p/terrastore/
Quick Start: http://code.google.com/p/terrastore/wiki/Documentation
Download: http://code.google.com/p/terrastore/downloads/list

• RavenDB: Raven is a .NET Linq enabled Document Database, focused on providing high performance, schema-less, flexible and scalable NoSQL data store for the .NET and Windows platforms.
  Raven store any JSON document inside the database. It is schema-less database where you can define indexes using C#’s Linq syntax.

Home: http://ravendb.net/
Quick Start: http://ravendb.net/tutorials
Download: http://ravendb.net/download

• OrientDB: OrientDB is an open source NoSQL database management system written in Java. Even if it is a document-based database, the relationships are managed as in graph databases with direct connections between records. It supports schema-less, schema-full and schema-mixed modes. It has a strong security profiling system based on users and roles and supports SQL as a query languages.

Home: http://www.orientechnologies.com/
Quick Start: http://code.google.com/p/orient/wiki/Tutorials
Download: http://code.google.com/p/orient/wiki/Download

• ThruDB: Thrudb is a set of simple services built on top of the Apache Thrift framework that provides indexing and document storage services for building and scaling websites. Its purpose is to offer web developers flexible, fast and easy-to-use services that can enhance or replace traditional data storage and access layers.
  It supports multiple storage backends such as BerkeleyDB, Disk, MySQL and also having     Memcache and Spread integration.

Home: http://code.google.com/p/thrudb/
Quick Start: http://thrudb.googlecode.com/svn/trunk/doc/Thrudb.pdf
Download: http://code.google.com/p/thrudb/source/checkout

• SisoDB:  SisoDb is a document-oriented db-provider for Sql-Server written in C#. It lets you store object graphs of POCOs (plain old clr objects) without having to configure any mappings. Each entity is treated as an aggregate root and will get separate tables created on the fly.

Home: http://www.sisodb.com
Quick Start: http://www.sisodb.com/Wiki
Download: https://github.com/danielwertheim/SisoDb-Provider/

• RaptorDB: RaptorDB is a extremely small size and fast embedded, noSql, persisted dictionary database using b+tree or MurMur hash indexing. It was primarily designed to store JSON data (see my fastJSON implementation), but can store any type of data that you give it.

Home: http://www.codeproject.com/KB/database/RaptorDB.aspx
Quick Start: http://www.codeproject.com/KB/database/RaptorDB.aspx
Download: http://www.codeproject.com/KB/database/RaptorDB.aspx

• CloudKit: CloudKit provides schema-free, auto-versioned, RESTful JSON storage with optional OpenID and OAuth support, including OAuth Discovery.

Home: http://getcloudkit.com/
Quick Start: http://getcloudkit.com/api/
Download: https://github.com/jcrosby/cloudkit

• Perservere: Persevere is an open source set of tools for persistence and distributed computing using an intuitive standards-based JSON interfaces of HTTP REST, JSON-RPC, JSONPath, and REST Channels. The core of the Persevere project is the Persevere Server. The Persevere server includes a Persevere JavaScript client, but the standards-based interface is intended to be used with any framework or client.

Home: http://code.google.com/p/persevere-framework/
Quick Start: http://code.google.com/p/persevere-framework/w/list
Download: http://code.google.com/p/persevere-framework/downloads/list

• Jackrabbit: The Apache Jackrabbit™ content repository is a fully conforming implementation of the Content Repository for Java Technology API (JCR, specified in JSR 170 and 283). A content repository is a hierarchical content store with support for structured and unstructured content, full text search, versioning, transactions, observation, and more.

Home: http://jackrabbit.apache.org
Quick Start: http://jackrabbit.apache.org/getting-started-with-apache-jackrabbit.html
Download: http://jackrabbit.apache.org/downloads.html

Conclusion:
Document databases store and retrieve documents and basic atomic stored unit is a document.  As always your requirement leads into the decision. You need to think about your data-access patterns / use-cases to create a smart document-model. When your domain model can be split and partitioned across some documents, a document-database will be a suitable one for you. For example for a blog-software, a CMS or a wiki-software a document-db works extremely well. But at the same time a non-relational database is not better than a relational one in some cases where  your database have a lot of relations and normalization.

Just check the following link from stackoverflow also to cover the pros/cons of Relational Vs Document based databases.
http://stackoverflow.com/questions/337344/pros-cons-of-document-based-databases-vs-relational-databases

“Your life today is the result of your attitudes and choices in the past. Your life tomorrow will be the result.”

This is a story of an elderly carpenter who had been working for a contractor for the past 53 years. He had built many beautiful houses but now as he was getting old, he wanted to retire and lead a leisurely life with his family. So, he goes to the contractor and tells him about his plan of retiring. The contractor feels sad at the prospect of losing a good worker but agrees to the plan because the carpenter had indeed become too fragile for the tough building work. But as a last request, he asks the old carpenter to construct just one last house.
The old man agrees and starts working but his heart was not in his work any more. He had lost the motivation towards work. So, he resorted to shoddy workmanship and constructed the house half-heartedly. After the house was built, the contractor came to visit his employee’s last piece of work. After inspecting the house, he handed over the front door keys to the carpenter and said, “This is your new house. My gift to you.” The carpenter was shocked and upset. Had he known that he was building his own house, he would have done a better job! Now, he would have to live in the house, which is not worth staying.
Think of yourself as the carpenter. You work hard every day but are you giving your best? We put our least to the work we don’t like or do not have interest in. Later, we get shocked at the situation we have created for ourselves and try to figure out why we didn’t do it differently.
Enjoy your tasks and carry on your responsibilities with pleasure and not with pain. “Life is a do-it-yourself project”. Do your job enthusiastically and with devotion, a positive output and a pleasing life will certainly be on your way.