Data Warehouse Appliances

Data Warehouse Appliances [DWA] were designed specifically to support streaming business intelligence [BI] workloads. They consist of architecturally integrated hardware, DBMS and storage into one device.

The aim of the DWA architecture is to combine the best elements of SMP and massively parallel processing [MPP] into one solution to optimize queries, and thereby removing bottlenecks to data flow.

By supporting a streaming data-flow, through standard interfaces, a data warehouse appliance is fully compatible with existing BI applications, tools and data. The only constraint to performance is the disk speed.

It has an extremely low total cost of ownership, requiring minimal system integration and administration. Data warehouse appliances are far simpler to install and maintain than a typical database and storage infrastructure.

To many data warehousing appliance and appliance-like systems are seen as 'disruptive innovations' in that they divert significantly from the norm. This has largely been fostered by certain claims that the promised super performance did not stack up when tested in a real life environment of complex, mixed workloads and multiple concurrent queries and updates.

This could well be the reason that Teradata has refused to adopt the 'appliance' term in reference to it massively parallel processing, shared nothing Active Data Warehouse. The ADW is a much greater innovation than simple DWA.

However, other claims demonstrate that processing 1.4TB of data [table - 5.7 billion rows], a data warehouse appliance will perform 20 times faster for less than half the total cost of a patchwork database system.

Typcially, the need for data warehouse appliances was justified in terms of a hierarchy of technology power needs:

DWA and Data Marts

Most data warehouse appliances support large data marts, integrated to analytic applications, focused on a single subject such as call-level detail, customers, shopping baskets etc.

Some CIO's use data marts as a strategic shield to introduce a data warehouse appliance into their data center with minimal risk. The appliance satisfies the analytic application’s requirements and also serves as a 'proof of concept' data warehouse.

DWA and EDW

Deploying an enterprise data warehouse [EDW] on an appliance is gaining support, where previously EDW's were more commonly deployed on data warehouse bundles.

Capacity

Large data marts usually manage between 1 TB and 10 TB of live, query-able data. This range is moving up as vendors introduce models of greater capacity. Appliances up to 20 TB are currently deployed

Regardless as to whether you view the data warehouse appliance market as pretty much over, the database innovation that it stirred will beneft standard relational technology going forward. IN the future, enterprises will need only one kind of database to perform both transactional and business intelligence processes, albeit many IT departments will continue to implement separate instances for reasons of operational efficiency.

DWA Integration

The DWA integrates with BI solutions and ETL tools using standardized interfaces, protocols and functionality. This includes interfaces with MicroStrategy, Business Objects, Cognos, SAS and SPSS.

ETL tool interfaces include Ab Initio, Ascential and Informatica.

The data warehouse appliance works seamlessly with these tools and applications as well as other in-house applications.

Key DWA Vendors

The key vendors for data warehouse appliances include:

• Netezza
• DATAllegro - two lines of appliances - capacity and performance

When to Use A Data Warehouse Appliance

A data warehouse appliance should be considered when a terabyte-size data mart supports an autonomous analytic application.

If the application involves intense ad hoc queries that place greater load on the organization’s enterprise data warehouse, then the DWA is even more appropriate.

Implementing a data warehouse appliance for an isolated analytic application is a low-risk way of proving the value of a data appliance in a data center.

They are also deployed in projects that require short time frames, low price per terabyte, and minimal system integration and administration.

Other Uses for Appliances

The use of data warehouse appliances is not unique to data warehousing. Appliances are also used in:

• Network Appliance [storage]
• Google Search Appliance
• Thunderstone Search Appliance
• Blade servers
• Network storage
• Other rack-mounted systems that resemble appliances.

Next: Netezza Performance Server [NPS]

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