Windows Azure Marketplace, “Denali” and SaaS Pricing

By Srinivasan Sundara Rajan	Article Rating:
July 15, 2011 11:15 AM EDT	Reads:	1,196

I have stressed the need for communities to help make the cloud market move toward the advantage of enterprises and, in particular, also provide more options for SaaS adoption. In this context, it is really good to see the Windows Azure Marketplace taking off and as a community for the collaboration among Windows Azure Cloud users.

As per Microsoft's vision, the Windows Azure Marketplace is a global online market for customers and partners to share, buy, and sell finished SaaS applications and premium datasets. Whether you're looking for new customers for your Windows Azure-based application or datasets, or are seeking new Windows Azure solutions to power your business, the Windows Azure Marketplace is a one-stop location supported by Microsoft to help you succeed.

The following are some of the useful categories of SaaS offerings in the Windows Azure Marketplace for enterprises:

Worldwide address verification and cleansing
High-granularity geocode for any address worldwide
D&B business lookup

Just to name a few, here's a full list of data services and applications that can be found on the vendor site.

Windows Azure Marketplace at Work
Recently Microsoft announced CTP 3 of SQL Server Codename "Denali," which includes a key new feature called Data Quality Services. Data Quality Services enables customers to cleanse their existing data stored in SQL databases, such as customer data stored in CRM systems that may contain inaccuracies created due to human error.

Data Quality Services leverages the Windows Azure Marketplace to access real-time data cleansing services from leading providers, such as Melissa Data, Digital Trowel, Loqate and CDYNE Corp.

We can analyze and write more about Data Quality Services integration in the future articles.

SaaS Pricing in Windows Azure Marketplace
Analysis of the pricing model of most of the SaaS-based services today revealed volume pricing based on the number of records. For example, Address Verification and Cleansing Services use a pricing model of:

100,000 Records Subscription
50,000 Records Subscription, etc.

Some other pricing is also based on transactions such as:

500,000 Transactions Per Month Subscription
200,000 Transactions Per Month Subscription

Again a transaction is defined as each page of results returned from a query uses a single transaction(tx) and will count toward your transaction limit. A page of results may return up to 100 records, but will never return more than 100 records.

Limitations of SaaS Pricing
Current mode of SaaS pricing has the following limitations with respect to large enterprises adopting them from a business perspective.

Pricing options are based on technical standards such as number of transactions
Tied to a particular technology architecture, for example, number of rows are a measure of relational databases and not for columnar analytical databases or big data unstructured databases
No clear way to compare SaaS pricing between two providers, for example, if one measures it on transactions and the other on rows, how can the enterprises choose the most optimal one?
Difficult to measure and predict the cost

Function Points-Based SaaS Pricing
The above thought process led to the reposting of my earlier article on SaaS Pricing with Function Points. It details out the Function Point-based serving of SaaS functionalities which could be the most viable option, because it is technology independent and the end users can clearly measure what they are served in terms of business functionalities.

More Stories By Srinivasan Sundara Rajan

Srinivasan Sundara Rajan works at Hewlett Packard as a Solution Architect. His primary focus is on enabling SOA through Legacy Modernization for Automobile Industries. He has worked as a consultant for Compuware, Verizon and other organizations in the earlier parts of career. All the views expressed are Srinivasan's independent analysis of industry and solutions and need not necessarily be of his current or past organizations. Srinivasan would like to thank every one who augmented his Architectural skills with Analytical ideas.

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