Oracle's Warehouse Builder ETL Tool Continues to Improve
27 January 2003
Ted Friedman

Document Type:  Research Note
Note Number:  P-19-1449

Among the major database management system vendors offering extraction, transformation and loading functionality, Oracle continues to lead. Several areas of weakness remain, but Warehouse Builder is moving in the right direction.

What You Need to Know

Oracle continues to improve Oracle Warehouse Builder (OWB) through regular releases, and customer successes are becoming more prevalent. Price remains a major driver for adoption, but functionality and ease of use are beginning to attract Oracle customers as well. As a result, we upgrade OWB's rating to "promising." Although the product is still considered unproven in highly complex data warehouse scenarios, enterprises with Oracle-centric data warehouse architectures and moderate complexity requirements should place OWB on their shortlists for extraction, transformation and loading tools.

Analysis

Oracle
Headquarters: Redwood Shores, California
Web Location: www.oracle.com
Founded: 1977
Ownership: Public
Employees: 41,496 (as of October 2002)
Financial Data: Revenue:
FY99, $8.8 billion; FY00, $10.1 billion; FY01, $10.9 billion; FY02, $9.67 billion

Strategic Planning Assumption
Through 2006, Oracle will continue to enhance OWB but, like the other major RDBMS vendors, will not completely close the gap in functionality compared to best-of-breed ETL offerings (0.8 probability).

Database management system (DBMS) vendors continue to exert influence on the extraction, transformation and loading (ETL) tools market, but with varying degrees of success (see "ETL Magic Quadrant Update: Market Pressure Increases"). Among the "Big Three" DBMS vendors (IBM, Microsoft and Oracle), Oracle has made the most progress, delivering regular enhancements to its Oracle Warehouse Builder (OWB) ETL tool and establishing a product road map supportive of its strategy. Although recent releases continue to close the gap in functionality vs. the best-of-breed leaders in the market, Oracle remains at a disadvantage in capabilities, "mind share" and "real world" proof points.

Positive Product Road Map: With Oracle9i Warehouse Builder and a subsequent point release, Oracle focused on shoring up metadata management functionality and delivering tighter integration with the Oracle applications. (OWB can now assimilate the metadata for all application modules to accelerate the design and deployment of marts and warehouses for which this data is the source.)

The next release of OWB, code-named "Calais," will be available with iDS (Oracle's developer suite of products) v.9.04, expected in April 2003 (0.8 probability).

Anticipated improvements to OWB in this release are:

• Simplified developer user interface for greater productivity
• Improved debugging capabilities
• Enhanced performance and scalability
• Increased integration with the rest of the Oracle business intelligence (BI) "stack" (for example, ability to share metadata with Discoverer)
• Enhanced metadata management capabilities

Throughout the product road map, data source support remains consistent — Oracle DBMS, any Open Database Connectivity (ODBC)-compliant data store, the Oracle Transparent Gateways (for DB2, Sybase, Informix and SQL Server) and flat files. The Oracle DBMS and flat files remain the only supported targets. Support for SAP R/3 data extraction is included with OWB via generated Advanced Business Application Programming (ABAP) code. Although OWB currently lacks support for bulk extract from mainframe data sources due to Oracle no longer supporting the Pure*Extract product, Oracle has stated it plans to deliver this functionality through an original equipment manufacturer arrangement in early 2003.

Several Points of Weakness Remain: Recent discussions with numerous Oracle customers using OWB confirm that the product is becoming more capable over time. However, Oracle is coming from far behind the market leaders in terms of functionality and cannot address all weaknesses immediately.

Functional areas for improvement include:

• Clarity and extensibility of error handling
• Robust debugging
• Need to minimize complexity of generated code
• Version control/management of object migration from test to production
• Consolidation of multiple repositories underneath the various products in the Oracle BI stack (this is not an OWB-specific limitation, but adds to the effort of deploying OWB)

OWB is being deployed at an increasing number of Oracle customer sites. Oracle estimates the installed base of OWB at 1,500 to 2,000 sites, although Gartner estimates that approximately 50 percent of these sites are in production. OWB users are generally sourcing data from Oracle databases and flat files only, with low to moderate complexity of transformations. Although uptake of the product is increasing, it remains rare to see OWB driving the entire data acquisition process for large, complex data warehouse implementations in heterogeneous data architectures. Regardless, based on the constant improvements in functionality and the positive direction of the product road map, we upgrade the overall rating of OWB to "promising" (see Note 1).

Note 1
Gartner's Vendor/Product Rating Scale
Strong Positive — Solid provider of strategic products, services or solutions.

• Customers: Continue investments.
• Potential customers: Consider this vendor a strong strategic choice.

Positive — Demonstrates strength in specific areas, but is largely opportunistic.

• Customers: Continue incremental investments.
• Potential customers: Put this vendor on a short list of tactical alternatives.

Promising — Shows potential in specific areas; however, initiative or vendor has not fully evolved or matured.

• Customers: Watch for a change in status and consider scenarios for short- and long-term impact.
• Potential customers: Plan for and be aware of issues and opportunities related to the evolution and maturity of this initiative or vendor.

Caution — Faces challenges in one or more areas.

• Customers: Understand challenges in relevant areas; assess short- and long-term benefit/risk to determine if contingency plans are needed.
• Potential customers: Note the vendor's challenges as part of due diligence.

Strong Negative — Difficulty responding to problems in multiple areas.

• Customers: Exit immediately.
• Potential customers: Consider this vendor only if there are no alternatives.

Product Strategy

Leverage core Oracle infrastructure components and push integration with other Oracle BI products to better support the "complete BI stack" message. Grow significant ETL market share and minimize direct competition with best-of-breed ETL vendors through attractive pricing and retention of Oracle-centric direction.

Strengths

• Built on mature Oracle infrastructure (PL/SQL, caching in Oracle DBMS)
• Allows Oracle customers to leverage investments in Oracle technology and skills (for example, PL/SQL)
• Low cost
• Integration with other components of Oracle BI stack

Challenges

• Grow ETL market share, despite limitations of Oracle-centric architecture
• Demonstrate value at high end of complexity scale
• Continue to expand support for heterogeneous environments — for example, packaged applications, non-Oracle targets, improved performance for non-Oracle relational database management system (RDBMS) sources
• Retain focus on and investment in R&D for OWB, despite the lack of a quantifiable direct revenue stream (due to bundling with other products in iDS)

Consider This Product When

• Enterprise has the majority of its data in Oracle DBMS, and will deploy data warehouses and data marts in Oracle DBMS
• Other components of the Oracle BI stack will be used
• Enterprise's data extract needs are primarily relational in nature
• Enterprise has Oracle skills (PL/SQL)

Consider Alternatives When

• Target DBMS for data warehouse/data marts will not be Oracle (or need to support more than one target DBMS)
• Data extract requirements include mainframe sources, packaged applications or significant percentage of non-Oracle data
• Highly complex integration and transformation operations are required

Key Issue
How can users strategically integrate and organize data for a data warehouse?

Acronym Key

This research is part of a set of related research pieces. See AV-19-2672 for an overview.

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