Featured White Papers

• Measuring Risk to Improve Java Software Quality
• Do You Really Get Classloaders?
• Pragmatic Continuous Delivery with Jenkins, Nexus, and LiveRebel
• Your Next Java Web App: Less XML, No Long Restarts, Fewer Hassles
• Coding with JRebel, Java Forever Changed
• 2012 Developer Productivity Report: Java Tools, Tech, Devs, and Data

Sponsored Links

• Graph databases are 1000x faster than relational.

  Learn More!

• Career opportunities at Harman- Careers That'll Rock Your Socks Off.

  Learn More!

• Developer-friendly Java PDF libraries by Qoppa Software

  Live Demos

• Stop blaming your app! Diagnose Java performance issues.

  Free tool >

• UrbanCode: Go From Continuous Integration to
  Continuous Delivery

  Learn More!

Sponsored Links

Optimize with a SATA RAID Storage Solution
Range of capacities as low as $1250 per TB. Ideal if you currently rely on servers/disks/JBODs

NoSQL showdown: MongoDB vs. Couchbase

Which NoSQL database has richer querying, indexing, and ease of use?

By Rick Grehan, InfoWorld, 03/21/13

Document databases may be the most popular NoSQL database variant of them all. Their great flexibility -- schemas can be grown or changed with remarkable ease -- makes them suitable for a wide range of applications, and their object nature fits in well with current programming practices. In turn, Couchbase Server and MongoDB have become two of the more popular representatives of open source document databases, though Couchbase Server is a recent arrival among the ranks of document databases.

In this context, the word "document" does not mean a word processing file or a PDF. Rather, a document is a data structure defined as a collection of named fields. JSON (JavaScript Object Notation) is currently the most widely used notation for defining documents within document-oriented databases. JSON's advantage as an object notation is that, once you comprehend its syntax -- and JSON is remarkably easy to grasp -- then you have all you need to define what amounts to the schema of a document database. That's because, in a document database, each document carries its own schema -- unlike an RDBMS, in which every row in a given table must have the same columns.

The latest versions of Couchbase Server and MongoDB are both newly arrived. In December 2012, Couchbase released Couchbase Server 2.0, a version that makes Couchbase Server a full-fledged document database. Prior to that release, users could store JSON data into Couchbase, but the database wrote JSON data as a blob. Couchbase was, effectively, a key/value database.

10gen released MongoDB 2.4 just this week. MongoDB has been a document database from the get-go. This latest release incorporates numerous performance and usability enhancements.

Both databases are designed to run on commodity hardware, as well as for horizontal scaling via sharding (in Couchbase, the rough equivalent to a shard is called a partition). Both databases employ JSON as the document definition notation, though in MongoDB, the notation is BSON (Binary JSON), a binary-encoded superset of JSON that defines useful data types not found in JSON. While both databases employ JavaScript as the primary data manipulation language, both provide APIs for all the most popular programming languages to allow applications direct access to database operations.

Key differences
Of course there are differences. First, MongoDB's handling of documents is better developed. This becomes most obvious in the mongo shell, which serves the dual purpose of providing a management and development window into a MongoDB database. Database, collections, and documents are first-class entities in the shell. Collections are actually properties on database objects.

For more enterprise computing news, visit InfoWorld. Story copyright InfoWorld Media Group, Inc.