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Navigating the Transition From Relational to NoSQL Database Technology

NAVIGATING THE TRANSITION FROM RELATIONAL TO NOSQL DATABASE TECHNOLOGY

Table of Contents
Introduction Why transition at all?
Scaling model Data model

3 3

The relational vs. document-oriented data model
Relational data model Document data model

4

Document Modeling: Rules of Thumb
Models (Primary) KeysMultiple Places and Editability Concurrency

6

Conclusion About Couchbase

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2 © 2012 COUCHBASE ALL RIGHTS RESERVED. WWW.COUCHBASE.COM

NAVIGATING THE TRANSITION FROM RELATIONAL TO NOSQL DATABASE TECHNOLOGY

Introduction
While the hype surrounding “NoSQL” (non-relational) database technology has become deafening, there is real substance beneath the often exaggerated claims.But like most things in life, the benefits come at a cost. Developers accustomed to data modeling and application development against relational database technology will need to approach things differently. This white paper highlights the differences between a relational database and a distributed document-oriented database, the implications for application development, and guidance that can easethe transition from relational to NoSQL database technology.

Why transition at all?
Change is hard and rarely undertaken unless it alleviates significant pain. The white paper NoSQL Database Technology provides a comprehensive look at the motivating challenges that have led to the emergence and rapid adoption of NoSQL database technology. In a nutshell, the transition has been spurred by theneed for flexibility – both in the scaling model and the data model.

Scaling model
Relational database technology is a “scale up” technology – to add capacity (whether data storage or I/O capacity) one gets a bigger server. The modern approach to application architecture is to scale out, rather than scale up. Instead of buying a bigger server, you add more commodity servers, virtual machines orcloud instances behind a load balancer. Conversely, capacity can be easily removed when no longer required. While scaling out is already common at the application logic tier, database technology is only now catching up.

Data model
The scale-out deployment benefits of NoSQL technology frequently get the most attention, but equally important are the benefits afforded by a schemaless approach todata management. With a relational database, you must define a schema before adding records to the database. Each record added to the database must adhere strictly to this schema with its fixed columns and data types. Changing the database schema, particularly when dealing with a partitioned relational database spread across many servers, is difficult. If your data capture and management needs areconstantly evolving, a rigid schema quickly becomes blocker to change. NoSQL databases (whether key-value, document, column-oriented or otherwise) scale out, and they don’t require schema definition prior to inserting data nor a schema change when data capture and management needs evolve. The rest of this paper will focus on distributed document-oriented NoSQL database technology – with Couchbaseand MongoDB being the two most visible and widely adopted examples.

3 © 2012 COUCHBASE ALL RIGHTS RESERVED. WWW.COUCHBASE.COM

NAVIGATING THE TRANSITION FROM RELATIONAL TO NOSQL DATABASE TECHNOLOGY

The relational vs. document-oriented data model
The figure below compares four records from a relational database with four from a document-oriented database.
{ “UUID”: “21f7f8de-8051-5b89-86“Time”: “2011-04-01T13:01:02.42 { “Server”: “A2223E”, “UUID”:“Calling Server”: “A2213W”, “21f7f8de-8051-5b89-86 “Time”: “Type”: “E100”, “2011-04-01T13:01:02.42 { “Server”:“Initiating User”: “dsallings@spy.net”, “A2223E”, “UUID”:“Calling Server”: “A2213W”, “21f7f8de-8051-5b89-86 “Details”: “Time”: “Type”: “E100”, “2011-04-01T13:01:02.42 { { “Server”:“Initiating User”: “dsallings@spy.net”,...