19.5 Test Results

   

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The benchmarking tests were run on an Intel Pentium III server with 450MHz, 256MB RAM, and two mirrored UW-SCSI hard disks. The clients included an Intel Pentium III processor with 350MHz and 128MB RAM. They were connected to the server by a 10-Mbit local area network. The storing strategies used a well-known relational DBMS, object-oriented DBMS, directory server, and native XML DBMS (for legal reasons the products cannot be named).

The documents used were automatically generated based on a DTD that defines the structure of project descriptions. The DTD contains 26 elements with a maximum nesting size of 8 and 4 attributes. XML documents based on this DTD contain information on the project members, such as names and addresses, as well as information on the publications, such as articles. This allows us to easily produce different-sized documents.

To compare the different database types, we run a set of tests that do the following:

• Store XML documents

• Extract complete XML documents

• Delete complete XML documents

• Extract parts of documents identified by the position of elements in the document

• Replace parts of documents

The benchmarks were specified and run by Fellhauer (see Fellhauer 2001 for the complete list of test results).

19.5.1 Evaluation of Performance

We ran the benchmarks five times with every document of every size, dropped the best and the worst results, and took the average of the remaining three values as the result value. Table 19.7 shows the results of storing XML documents.

All figures in Table 19.7 measure the times for inserting the XML document into the database including the time consumed by the DOM parser. The object-oriented database is the best. The native XML database shows a relatively high growth rate, which we could not confirm for larger documents because of the limited space of our test installation?an 11MB document took 35MB disk space of the 50MB space of the test version. Almost surprising is the bad result of storing the 25MB document into the typed relational database: It took more than 12 hours. We would like to investigate this further to determine if the number of tables involved is the reason. We were not able to store the 64MB document in the databases due to the 256MB main memory. The DOM tree could be built, but the traversal of the tree resulted in permanent swapping. Table 19.8 shows the results of extracting complete XML documents.

^[*] Failed because of license restrictions.

The native XML database shows the best results, better than the directory server, which is known for its fast read access. It is not surprising that the relational databases consume a lot of time for reconstructing the documents. We do not know whether the size of the unique element table in the nontyped relational database will produce a result worse than the typed relational database result. The number of tables could influence the results for the 8MB document, especially when we apply proprietary statements for selecting hierarchically connected entries.

To extract parts of the XML documents, we ran queries that determine elements in the XML document and return these elements or parts of their content. All databases show similar results independent of the size of the document; there is no sequential search. The relational databases are the fastest, where the difference between the nontyped and the typed approaches is due to the runtime of consulting the DTD. Table 19.9 shows the test results for the query "Select the first heading of the third publication of a project determined by a project number."

The nontyped relational database shows surprisingly good results especially for the selection of small document parts. It leaves the directory servers, which are known for fast read accesses, far behind. The poor results of the object database are caused by the reconstruction and searching of the DOM tree.

Table 19.8. Test Results for Extracting Complete XML Documents

Size of XML Documents	Directory Server	Non-Typed Relational Database	Typed Relational Database	Object-Oriented Database	Native XML Database
125 KB	11.8 s	26.9 s	31.0 s	12.9 s	8.7 s
500 KB	22.2 s	81.1 s	75.9 s	26.5 s	9.5 s
2,000 KB	39.1 s	307.4 s	275.6 s	49.9 s	12.7 s
8,000 KB	153.4 s	2,369.7 s	1,620.3 s	175.2 s	28.7 s
16,000 KB	206.7 s	-	-	232.2 s	-
32,000 KB	413.4 s	-	-	904.2 s	-

Table 19.9. Test Results for Extracting Parts of XML Documents

Size of XML Documents	Directory Server	Non-Typed Relational Database	Typed Relational Database	Object-Oriented Database	Native XML Database
125 KB	3.7 s	0.2 s	3.4 s	12.9 s	8.9 s
500 KB	3.6 s	0.2 s	3.6 s	24.9 s	9.5 s
2,000 KB	3.7 s	0.2 s	3.5 s	45.4 s	12.4 s
8,000 KB	3.8 s	0.2 s	3.6 s	154.4 s	235.1 s
16,000 KB	3.6 s	0.2 s	3.5 s	199.7 s	-
32,000 KB	3.6 s	-	-	396.7 s	-

Finally, Table 19.10 shows the results of updating parts of an XML document?for example, the whole person element determined by the last name and the project number should be replaced by a new person element given as are XML document.

The native XML database shows dramatically decreasing performance. The poor results of the object database are due to the bad performance of the search functions applied to the persistent DOM tree.

Table 19.10. Test Results for Replacing Parts of an XML Document

Size of XML Documents	Directory Server	Non-Typed Relational Database	Typed Relational Database	Object-Oriented Database	Native XML Database
125 KB	17.8 s	7.3 s	5.9 s	809.0 s	19.6 s
500 KB	17.3 s	7.2 s	5.8 s	798.9 s	52.0 s
2,000 KB	17.2 s	7.3 s	5.8 s	798.7 s	195.9 s
8,000 KB	17.2 s	7.2 s	5.8 s	794.4 s	198.9 s
16,000 KB	17.1 s	7.4 s	5.6 s	796.7 s	692.3 s
32,000 KB	16.9 s	-	-	795.8 s	-

19.5.2 Evaluation of Space

Table 19.11 shows the disk space each database management system uses to store the schema and the XML documents of different sizes. The typed relational database approach defines a table for each element type, which increases space for the schema. However, disk space to store the XML documents is very efficient.

The directory server and the native XML database produce a lot of overhead, when compared to the original XML document.

19.5.3 Conclusion

The benchmarks have shown that the nontyped relational database approach has advantages over all other solutions. The weak point is the reconstruction of complete XML documents, which should be improved. As long as a standardized XML query language does not support inserting and updating functionality, the reconstruction of XML documents will be an important operation.

We do not know whether the bad results of the searching function of the object-oriented database system are representative for this database type. But it supports our belief that searching large object trees will cause large loading times due to the techniques the systems apply. To avoid this, special indexing techniques like B-trees have to be applied. Although content management systems based on object-oriented databases implement this improvement, we used the bare object-oriented database approach to show its capabilities.

Table 19.11. Disk Space Usage in Kilobytes

Size of XML Documents	Directory Server	Non-Typed Relational Database	Typed Relational Database	Object-Oriented Database	Native XML Database
Schema/0 KB	440	672	3,484	512	5,178
125 KB	2,064	117	118	615	760
500 KB	4,952	820	546	1,536	2,088
2,000 KB	11,240	3,164	2,182	3,738	7,060
8,000 KB	40,848	15,157	10,547	13,722	28,780
16,000 KB	53,280	26,562	18,476	22,630	> 50,000[*]
32,000 KB	120,024	-	-	43,991	-
64,000 KB	-	-	-	-	-

^[*] Space restriction of 50 MB.

The directory server shows disappointing results compared to the relational database. The expected very fast reading times could not be achieved. There might be some improvements in the mapping of the DOM tree into the directory information tree, too. Also the space consumed by the directory server is critical. Additional experiments will be necessary to determine the reasons.

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Top Title TOC Preface P.1 What Is XML? P.2 XML Concepts P.3 XML-Related Technologies P.4 XML Data Management P.5 How This Book Is Organized P.6 Who Should Read This Book P.7 Resources Acknowledgments Chapter 8 Chapter 12 Chapter 13 Chapter 14 Chapter 19 Part I: What Is XML? Chapter 1. Information Modeling with XML 1.1 Introduction 1.2 XML as an Information Domain 1.3 How XML Expresses Information 1.4 Patterns in XML 1.5 Common XML Information-Modeling Pitfalls 1.6 A Very Simple Way to Design XML 1.7 Conclusion Part II: Native XML Databases Chapter 2. Tamino-Software AG's Native XML Server 2.1 Introduction 2.2 Tamino Architecture and APIs 2.3 XML Storage 2.4 Querying XML 2.5 Tools 2.6 Full Database Functionality 2.7 Conclusion Chapter 3. eXist Native XML Database 3.1 Introduction 3.2 Features 3.3 System Architecture Overview 3.4 Getting Started 3.5 Query Language Extensions 3.6 Application Development 3.7 Technical Background 3.8 Conclusion Chapter 4. Embedded XML Databases 4.1 Introduction 4.2 A Primer on Embedded Databases 4.3 Embedded XML Databases 4.4 Building Applications for Embedded XML Databases 4.5 Conclusion Part III: XML and Relational Databases Chapter 5. IBM XML-Enabled Data Management Product Architecture & Technology 5.1 Introduction 5.2 Product and Technology Offering Summaries 5.3 Current Architecture and Technology 5.4 Future Architecture and Technology 5.5 Conclusion Notices Chapter 6. Supporting XML in Oracle9i 6.1 Introduction 6.2 Storing XML as CLOB 6.3 XMLType 6.4 Using XSU for Fine-Grained Storage 6.5 Building XML Documents from Relational Data 6.6 Web Access to the Database 6.7 Special Oracle Features 6.8 Conclusion Chapter 7. XML Support in Microsoft SQL Server 2000 7.1 Introduction 7.2 XML and Relational Data 7.3 XML Access to SQL Server 7.4 Serializing SQL Query Results into XML 7.5 Providing Relational Views over XML 7.6 SQLXML Templates 7.7 Providing XML Views over Relational Data 7.8 Conclusion Chapter 8. A Generic Architecture for Storing XML Documents in a Relational Database 8.1 Introduction 8.2 System Architecture 8.3 The Data Model 8.4 Creating the Database 8.5 Connecting to the Repository 8.6 Uploading XML Documents 8.7 Querying the Repository 8.8 Further Enhancements 8.9 Conclusion Chapter 9. An Object-Relational Approach to Building a High-Performance XML Repository 9.1 Introduction 9.2 Overview of XML Use-Case Scenario 9.3 High-Level System Architecture 9.4 Detailed Design Descriptions 9.5 Conclusion Part IV: Applications of XML Chapter 10. Knowledge Management in Bioinformatics 10.1 Introduction 10.2 A Brief Molecular Biology Background 10.3 Life Sciences Are Turning to XML to Model Their Information 10.4 A Genetic Information Model 10.5 NeoCore XMS* 10.6 Integration of BLAST into NeoCore XMS Conclusion Chapter 11. Case Studies of XML Used with IBM DB2 Universal Database 11.1 Introduction 11.2 Case Study 1: "Our Most Valued Customers Come First" 11.3 Case Study 2: "Improve Cash Flow" 11.4 Conclusion Notices Chapter 12. The Design and Implementation of an Engineering Data Management System Using XML and J2EE 12.1 Introduction 12.2 Background and Requirements 12.3 Overview 12.4 Design Choices 12.5 Future Directions 12.6 Conclusion Chapter 13. Geographical Data Interchange Using XML-Enabled Technology within the GIDB System 13.1 Introduction 13.2 GIDB METOC Data Integration 13.3 GIDB Web Map Service Implementation 13.4 GIDB GML Import and Export 13.5 Conclusion Chapter 14. Space Wide Web by Adapters in Distributed Systems Configuration from Reusable Components 14.1 Introduction 14.2 Advanced Concept Description: The Research Problem 14.3 Integration of Components with Architecture 14.4 Example 14.5 Future Generation NASA Institute for Advanced Concepts, Space Wide Web Research, and Boundaries 14.6 Advanced Concept Development 14.7 Conclusion Chapter 15. XML as a Unifying Framework for Inductive Databases 15.1 Introduction 15.2 Past Work 15.3 The Proposed Data Model: XDM 15.4 Benefits of XDM 15.5 Toward Flexible and Open Systems 15.6 Related Work 15.7 Conclusion Chapter 16. Designing and Managing an XML Warehouse 16.1 Introduction 16.2 Architecture 16.3 Data Warehouse Specification 16.4 Managing the Metadata 16.5 Storage and Management of the Data Warehouse 16.6 DAWAX: A Graphic Tool for the Specification and Management of a Data Warehouse 16.7 Related Work 16.8 Conclusion Part V: Performance and Benchmarks Chapter 17. XML Management System Benchmarks 17.1 Introduction 17.2 Benchmark Specification 17.3 Benchmark Data Set 17.4 Existing Benchmarks for XML 17.5 Conclusion Chapter 18. The Michigan Benchmark: A Micro-Benchmark for XML Query Performance Diagnostics 18.1 Introduction 18.2 Related Work 18.3 Benchmark Data Set 18.4 Benchmark Queries 18.5 Using the Benchmark 18.6 Conclusion Chapter 19. A Comparison of Database Approaches for Storing XML Documents 19.1 Introduction 19.2 Data Models for XML Documents 19.3 Databases for Storing XML Documents 19.4 Benchmarking Specification 19.5 Test Results 19.6 Related Work 19.7 Summary Chapter 20. Performance Analysis between an XML-Enabled Database and a Native XML Database 20.1 Introduction 20.2 Related Work 20.3 Methodology 20.4 Database Design 20.5 Discussion 20.6 Experiment Result 20.7 Conclusion Chapter 21. Conclusion References Contributors Editors Chapter 1: Information Modeling with XML Chapter 2: Tamino-Software AG's Native XML Server Chapter 3: eXist Native XML Database Chapter 4: Embedded XML Databases Chapter 5: IBM XML-Enabled Data Management Product Architecture and Technology Chapter 6: Supporting XML in Oracle9i Chapter 7: XML Support in Microsoft SQL Server 2000 Chapter 8: A Generic Architecture for Storing XML Documents in a Relational Database Chapter 9: An Object-Relational Approach to Building a High-Performance XML Repository Chapter 10: Knowledge Management in Bioinformatics Chapter 11: Case Studies of XML Used with IBM DB2 Universal Database Chapter 12: The Design and Implementation of an Engineering Data Management System Using XML and J2EE Chapter 13: Geographical Data Interchange Using XML-Enabled Technology within the GIDB System Chapter 14: Space Wide Web by Adapters in Distributed Systems Configuration from Reusable Components Chapter 15: XML as a Unifying Framework for Inductive Databases Chapter 16: Designing and Managing an XML Warehouse Chapter 17: XML Management System Benchmarks Chapter 18: The Michigan Benchmark: A Micro-Benchmark for XML Query Performance Diagnostics Chapter 19: A Comparison of Database Approaches for Storing XML Documents Chapter 20: Performance Analysis between an XML-Enabled Database and a Native XML Database Remember the name: eTutorials.org Copyright eTutorials.org 2008-2023. 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