What is Mongo DB ? & why is it causing so much buzz in IT industry ?

What is Mongo DB ?

The wiki page quotes MongoDB (from "humongous") is a cross-platform document-oriented database.
Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is free and open-source software.

Why is creating so much of Buzz around ?

MongoDB is great for modeling many of the entities that back most modern web-apps, either consumer or enterprise:

Account and user profiles: can store arrays of addresses with ease
CMS: the flexible schema of MongoDB is great for heterogeneous collections of content types
Form data: MongoDB makes it easy to evolve the structure of form data over time
Blogs / user-generated content: can keep data with complex relationships together in one object
Messaging: vary message meta-data easily per message or message type without needing to maintain separate collections or schemas
System configuration: just a nice object graph of configuration values, which is very natural in MongoDB
Log data of any kind: structured log data is the future
Graphs: just objects and pointers – a perfect fit
Location based data: MongoDB understands geo-spatial coordinates and natively supports geo-spatial indexing

MongoDB is popular because it attracts the former PHP/MySQL programmer swamp.

Performance, speed and easy to manipulate database are advantages of mongodb to mysql.

MAIN FEATURES :

Document-oriented: Instead of taking a business subject and breaking it up into multiple relational structures, MongoDB can store the business subject in the minimal number of documents. For example, instead of storing title and author information in two distinct relational structures, title, author, and other title-related information can all be stored in a single document called Book, which is much more intuitive and usually easier to work with.
Ad hoc queries: MongoDB supports search by field, range queries, regular expression searches. Queries can return specific fields of documents and also include user-defined JavaScript functions.
Indexing: Any field in a MongoDB document can be indexed (indices in MongoDB are conceptually similar to those in RDBMSes). Secondary indices are also available.
Replication: MongoDB provides high availability with replica sets. A replica set consists of two or more copies of the data. Each replica set member may act in the role of primary or secondary replica at any time. The primary replica performs all writes and reads by default. Secondary replicas maintain a copy of the data on the primary using built-in replication. When a primary replica fails, the replica set automatically conducts an election process to determine which secondary should become the primary. Secondaries can also perform read operations, but the data is eventually consistent by default.
Load balancing: MongoDB scales horizontally using sharding. The user chooses a shard key, which determines how the data in a collection will be distributed. The data is split into ranges (based on the shard key) and distributed across multiple shards. (A shard is a master with one or more slaves.); MongoDB can run over multiple servers, balancing the load and/or duplicating data to keep the system up and running in case of hardware failure. Automatic configuration is easy to deploy, and new machines can be added to a running database.
File storage: MongoDB can be used as a file system, taking advantage of load balancing and data replication features over multiple machines for storing files.

This function, called GridFS, is included with MongoDB drivers and available with no difficulty for development languages (see "Language Support" for a list of supported languages). MongoDB exposes functions for file manipulation and content to developers. GridFS is used, for example, in plugins for NGINX and lighttpd. Instead of storing a file in a single document, GridFS divides a file into parts, or chunks, and stores each of those chunks as a separate document.

In a multi-machine MongoDB system, files can be distributed and copied multiple times between machines transparently, thus effectively creating a load-balanced and fault-tolerant system.

Aggregation: MapReduce can be used for batch processing of data and aggregation operations. The aggregation framework enables users to obtain the kind of results for which the SQL GROUP BY clause is used.
Server-side JavaScript execution: JavaScript can be used in queries, aggregation functions (such as MapReduce), and sent directly to the database to be executed.
Capped collections: MongoDB supports fixed-size collections called capped collections. This type of collection maintains insertion order and, once the specified size has been reached, behaves like a circular queue.