SlideShare ist ein Scribd-Unternehmen logo
1 von 44
XQuery’s Enigmatic Information Architecture Role  MarkLogic User Conference 2011 Peter O’Kelly peter@okellyassociates.com
Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 2
Background Where I’m coming from Industry analyst/consultant working in information management and collaboration domains for ~30 years Background Application developer and data architect Product management and strategy roles at Lotus, IBM, Groove Networks, Macromedia, and Microsoft Industry analyst/consultant with the Patricia Seybold Group and Burton Group pbokelly.blogspot.com 4/28/2011 © 2011 O’Kelly Associates 3
Background My high-level XQuery perspective XQuery truly is awesome… A very well-designed language and standards initiative, optimized for un- or semi-structured information But XQuery appears to be somewhat stalled, in terms of overall market momentum It’s important to understand and address the reasons for the stall Because a vibrant XQuery standard, along with related techniques and tools, are important for the evolution of information management 4/28/2011 © 2011 O’Kelly Associates 4
Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 5
Why XQuery is Awesome A purpose-built XML content manipulation language Gracefully applying the joy of sets to XML content Offering a sustainably complementary fit with SQL Designed by experts including SQL co-author Don Chamberlin Evolving to go far beyond queries With search, conditional expressions, function libraries, and more Can replace a kitchen sink of earlier technologies Fewer moving parts means more simplicity and less maintenance A W3C Recommendation, building on XML Schema, XPath, and other standards 4/28/2011 © 2011 O’Kelly Associates 6
Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 8
Other Evidence of Non-Mainstreaming Vendor uncertainty or other hesitation E.g., at Gilbane Boston 2010, few of the exhibitors I spoke with had even heard of XQuery Not a statistically significant survey, but still surprising Few of the current market-leading collaboration/ content platforms are based on XQuery Tangent: this suggests there is a compelling market opportunity for new collaboration/content entrants that are XQuery-based 4/28/2011 © 2011 O’Kelly Associates 14
Exploring the XQuery Enigma Some issues that have probably limited XQuery market momentum Lack of a big-picture framework Installed base inertia Standards and politics The Internet ethos Limited techniques and tools [Don’t panic!  We’ll return to the future-optimistic themes in a few minutes...] 4/28/2011 © 2011 O’Kelly Associates 15
A Big-picture Framework A digital information item dichotomy  Resources Digital artifacts optimized for human comprehension Organized in terms of narrative, hierarchy, and sequence Examples: books, magazines, documents (e.g., PDF, Word), Web pages, XBRL documents…  Relations Application-independent descriptions of real-world things and relationships Examples: business domain databases, e.g., customer, sales, HR… 4/28/2011 © 2011 O’Kelly Associates 16
The Resource/Relation Continuum 4/28/2011 © 2011 O’Kelly Associates 17 PDF docs XBRL docs Word docs DITA docs Desktop db Streaming db Operational db
A Big-picture Framework Complementary levels of modeling abstraction Conceptual Technology-neutral Used to establish contextual consensus  Also very useful, when done well, for creating logical models Logical Captures conceptual models in a technology rendering Examples: (beyond-the-basics) hypertext and relational Information workers and app developers ideally work at this level of abstraction Physical Includes implementation-level details Ideally, activity at this level is limited to system architects and administrators 4/28/2011 © 2011 O’Kelly Associates 18
Conceptual Model Examples 4/28/2011 © 2011 O’Kelly Associates 19
A Big-picture Framework 4/28/2011 © 2011 O’Kelly Associates 20
The Lack of a Big-picture Framework Without a framework, there’s likely to be Uncertainty about what to use when Conflict based more on miscommunication and/or misunderstanding than real issues Insufficient focus on  Application/data independence Conceptual/logical/physical model independence Low probability of appreciation for the sustainable and complementary fit between XQuery and SQL  4/28/2011 © 2011 O’Kelly Associates 21
Installed Base Inertia Incumbent vendors DBMS vendors Application vendors Large organizations usually have distinct “content” and “data” management groups, often with little collaboration between them Content-focused people are often more instance-oriented and care a lot about schema flexibility Database-focused people are generally more type-oriented and care a lot about schema precision 4/28/2011 © 2011 O’Kelly Associates 22
A Content-centric View 4/28/2011 © 2011 O’Kelly Associates 23
A Database-centric View 4/28/2011 © 2011 O’Kelly Associates 24
Installed Base Inertia Programmer preferences can be pernicious Object-oriented frameworks have a lot in common with resources (e.g., hierarchy, sequence, and positional navigation) The object/relational “impedance mismatch” is still irksome, in some tools/frameworks But that does not mean it’s reasonable to default to resource-oriented approaches for all domains, even if the application is XML-centric, because not all XML content is resource-centric Doing so can dumb-down DBMS usage patterns, with significant consequences 4/28/2011 © 2011 O’Kelly Associates 25
Standards and Politics “The nice thing about standards is that you have so many to choose from”  Andrew Tanenbaum As in the development of SQL, there are complex challenges at the intersection of standards groups, vendor agendas, and academic priorities The Open XML/ODF debate is another recent, relevant, and revealing case study 4/28/2011 © 2011 O’Kelly Associates 26
Standards and Politics NoSQL “A rhetorically clever and manipulative name … Saying ‘NoSQL’ says what you’re against, not what you’re for” (Joe Maguire) As with the largely failed “object database” wave 20+ years ago, NoSQL extremists appear to underestimate the expressive power and utility of what they propose to displace While there is ample room for database-related innovation, polarizing the debate is unhelpful 4/28/2011 © 2011 O’Kelly Associates 27
The Internet Ethos Lots to like Open, community-driven, vendor-independent… But also some risks; e.g., the Internet Doesn’t complain if your system is inefficient or ineffective  Is culturally conducive to cyber-polarization E.g., there are probably still lively Internet forum debates about the relative merits of DTD, Schematron, RNG, and XML Schema  And xBASE versus SQL, and RPG versus COBOL… This creates a key challenge: it’s difficult to get vitality readings on standards and technology alternatives Including major initiatives such as XQuery and XHTML 2.0 4/28/2011 © 2011 O’Kelly Associates 28
Limited Techniques and Tools Some SQL reality checks  Relatively few people work directly with SQL The vast majority of information workers and developers who benefit from using SQL do so indirectly, through tools ranging from IDEs to query/reporting applications The development of ODBC was pivotal for software vendors and application developers working with RDBMSs Making it possible for them to use a single interface model for multiple products 4/28/2011 © 2011 O’Kelly Associates 29
Limited Techniques and Tools XQuery's market uptake has been constrained by the small number of XQuery-based tools and applications  Which is in turn limited in part by the lack of a successful ODBC equivalent for XQuery Which, in turn, is partly a function of Microsoft’s apparent XQuery ambivalence  Many XML-focused developers believe they get most of what they need from XPath Without tools to promote effective use of XQuery, it’s a difficult value proposition to make 4/28/2011 © 2011 O’Kelly Associates 30
Limited Techniques and Tools Modeling techniques and tools are also pivotal There are some good options today for physical database modeling But few choices for logical modeling And almost a complete lack of conceptual modeling tools For XML information modeling, there are even fewer modeling technique/tool options today It’s also a cultural and incentive system challenge If developers are paid to primarily focus on physical models, that’s what most of them will do 4/28/2011 © 2011 O’Kelly Associates 31
Limited Techniques and Tools Many XML-focused developers appear to believe they don’t need to invest time and attention in modeling In part because XML-focused application development often starts with existing XML schemas and/or documents rather than “green field” modeling But modeling is equally applicable to resource and relation domains, for Establishing contextual consensus Helping to promote Application/information independence Conceptual/logical/physical model independence Fostering the effective application of set theory and maximizing the use of declarative expressions 4/28/2011 © 2011 O’Kelly Associates 32
Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 33
Projections and Recommendations XQuery is going to be a mainstream success RDBMSs aren’t going away anytime soon The standards scene is evolving in subtly significant ways More and better modeling MarkLogic is very well positioned 4/28/2011 © 2011 O’Kelly Associates 34
XQuery Will be a Mainstream Success And already is a success, for many progressive IT organizations and software vendors The next wave of XQuery momentum will likely come more from content management than traditional database management  Providing significant opportunities to have fewer information architecture moving parts E.g., to spend less on specialized enterprise content management, records management, and Web content management servers and tools 4/28/2011 © 2011 O’Kelly Associates 35
XQuery Will be a Mainstream Success Recommendations Learn and fully leverage XQuery Go beyond the basics to master the full XQuery language “Querying XML,” by Jim Melton and Stephen Buxton, is a useful resource in this context  Seek to simplify and consolidate, e.g.,   To do less scripting/programming and more declarative development using XQuery To migrate content and apps from legacy ECM systems 4/28/2011 © 2011 O’Kelly Associates 36
RDBMSs Aren’t Going Away Resources and relations are complementary And XQuery and SQL offer very strong synergy Systems such as Google’s Megastore are important leading indicators, as hybrid models “NoSQL” will rapidly evolve  Initially implied “Just say ‘no’ to SQL” Later quietly redefined as “Not Only SQL” What may be next: “New Opportunities for SQL” I.e., some developers may reconsider the value of SQL and RDBMSs, after hitting NoSQL limitations 4/28/2011 © 2011 O’Kelly Associates 37
RDBMSs Aren’t Going Away Recommendations Develop expertise in both (beyond-the-basics) hypertext and relational models And explore the information flows between them Provide clear customer requirements and feedback to your RDBMS, application, and tool vendors Encourage them to fully exploit resource/relation synergy Establish clear developer criteria on what to use when, e.g., for NoSQL alternatives Consider applying the framework presented earlier 4/28/2011 © 2011 O’Kelly Associates 38
Subtly Significant Standards Evolution The industry is a very different place compared to when SQL was standardized in the mid-1980s The Internet ethos is pervasive, and key vendors have learned to productively play the standards game together There have been some major standards changes recently, e.g., the discontinuation of XHTML 2.0 But there is also clear market momentum consolidation around standards including XML Schema, XPath 2.0, XSLT, and HTML5 And, although not always obviously, XQuery  4/28/2011 © 2011 O’Kelly Associates 39
Subtly Significant Standards Evolution Recommendations Place well-informed standards bets, regularly check assumptions, and be willing to make course corrections Get involved  Make your standards-related requirements clear to your strategic vendors Actively participate in standards activities 4/28/2011 © 2011 O’Kelly Associates 40
More and Better Modeling Conceptual, logical, and physical modeling are critical success factors for both resources and relations Organizations that under-invest in modeling are essentially reverting to the obsolete programs-have-files approach, limiting Application/data (and content) independence Conceptual/logical/physical model independence 4/28/2011 © 2011 O’Kelly Associates 41
More and Better Modeling Recommendations Develop modeling expertise  Explore resources such as “Mastering Data Modeling” (Carlis/Maguire) Apply the big-picture framework for consensus on (resources + relations) * (conceptual/logical/physical) Build and consistently use model repositories  Also ensure modeling and reuse are supported by developer incentive systems Provide clear modeling-related requirements to your tool and server vendors 4/28/2011 © 2011 O’Kelly Associates 42
MarkLogic is Very Well Positioned MarkLogic  Placed an early bet on XQuery, and continued to focus on XQuery while many other vendors balked  Has insights from XML information management market leadership in key domains including media, government, and finance Is led by a deeply experienced and strong team Recommendations Share your experiences this week and consider proposing a customer case study for MLUC 2012 4/28/2011 © 2011 O’Kelly Associates 43
Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 44

Weitere ähnliche Inhalte

Was ist angesagt?

Applying Big Data Superpowers to Healthcare
Applying Big Data Superpowers to HealthcareApplying Big Data Superpowers to Healthcare
Applying Big Data Superpowers to HealthcarePaul Boal
 
Data Lakehouse, Data Mesh, and Data Fabric (r2)
Data Lakehouse, Data Mesh, and Data Fabric (r2)Data Lakehouse, Data Mesh, and Data Fabric (r2)
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
 
BarbaraZigmanResume 2016
BarbaraZigmanResume 2016BarbaraZigmanResume 2016
BarbaraZigmanResume 2016bzigman
 
Dataiku Data Science Studio (datasheet)
Dataiku Data Science Studio (datasheet)Dataiku Data Science Studio (datasheet)
Dataiku Data Science Studio (datasheet)John Cann
 
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
 
Data Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to MeshData Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to MeshJeffrey T. Pollock
 
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization Denodo
 
Privacy-Preserving AI Network - PlatON 2.0
Privacy-Preserving AI Network - PlatON 2.0 Privacy-Preserving AI Network - PlatON 2.0
Privacy-Preserving AI Network - PlatON 2.0 ShiHeng1
 
Data Virtualization: From Zero to Hero
Data Virtualization: From Zero to HeroData Virtualization: From Zero to Hero
Data Virtualization: From Zero to HeroDenodo
 
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...Jochem van Grondelle
 
Future of Data Platform in Cloud Native world
Future of Data Platform in Cloud Native worldFuture of Data Platform in Cloud Native world
Future of Data Platform in Cloud Native worldSrivatsan Srinivasan
 
The Curse of the Data Lake Monster
The Curse of the Data Lake MonsterThe Curse of the Data Lake Monster
The Curse of the Data Lake MonsterThoughtworks
 
What is the future of data strategy?
What is the future of data strategy?What is the future of data strategy?
What is the future of data strategy?Denodo
 
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...Databricks
 
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data VirtualityBeyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data VirtualityDataconomy Media
 
Modern Big Data Analytics Tools: An Overview
Modern Big Data Analytics Tools: An OverviewModern Big Data Analytics Tools: An Overview
Modern Big Data Analytics Tools: An OverviewGreat Wide Open
 
Use dependency injection to get Hadoop *out* of your application code
Use dependency injection to get Hadoop *out* of your application codeUse dependency injection to get Hadoop *out* of your application code
Use dependency injection to get Hadoop *out* of your application codeDataWorks Summit
 
Big data analytic platform
Big data analytic platformBig data analytic platform
Big data analytic platformJesse Wang
 

Was ist angesagt? (20)

Hadoop dev 01
Hadoop dev 01Hadoop dev 01
Hadoop dev 01
 
Applying Big Data Superpowers to Healthcare
Applying Big Data Superpowers to HealthcareApplying Big Data Superpowers to Healthcare
Applying Big Data Superpowers to Healthcare
 
Data Lakehouse, Data Mesh, and Data Fabric (r2)
Data Lakehouse, Data Mesh, and Data Fabric (r2)Data Lakehouse, Data Mesh, and Data Fabric (r2)
Data Lakehouse, Data Mesh, and Data Fabric (r2)
 
Destroying Data Silos
Destroying Data SilosDestroying Data Silos
Destroying Data Silos
 
BarbaraZigmanResume 2016
BarbaraZigmanResume 2016BarbaraZigmanResume 2016
BarbaraZigmanResume 2016
 
Dataiku Data Science Studio (datasheet)
Dataiku Data Science Studio (datasheet)Dataiku Data Science Studio (datasheet)
Dataiku Data Science Studio (datasheet)
 
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014
 
Data Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to MeshData Mesh Part 4 Monolith to Mesh
Data Mesh Part 4 Monolith to Mesh
 
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
DAMA & Denodo Webinar: Modernizing Data Architecture Using Data Virtualization
 
Privacy-Preserving AI Network - PlatON 2.0
Privacy-Preserving AI Network - PlatON 2.0 Privacy-Preserving AI Network - PlatON 2.0
Privacy-Preserving AI Network - PlatON 2.0
 
Data Virtualization: From Zero to Hero
Data Virtualization: From Zero to HeroData Virtualization: From Zero to Hero
Data Virtualization: From Zero to Hero
 
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
To mesh or mess up your data organisation - Jochem van Grondelle (Prosus/OLX ...
 
Future of Data Platform in Cloud Native world
Future of Data Platform in Cloud Native worldFuture of Data Platform in Cloud Native world
Future of Data Platform in Cloud Native world
 
The Curse of the Data Lake Monster
The Curse of the Data Lake MonsterThe Curse of the Data Lake Monster
The Curse of the Data Lake Monster
 
What is the future of data strategy?
What is the future of data strategy?What is the future of data strategy?
What is the future of data strategy?
 
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...
Data Mesh in Practice: How Europe’s Leading Online Platform for Fashion Goes ...
 
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data VirtualityBeyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
 
Modern Big Data Analytics Tools: An Overview
Modern Big Data Analytics Tools: An OverviewModern Big Data Analytics Tools: An Overview
Modern Big Data Analytics Tools: An Overview
 
Use dependency injection to get Hadoop *out* of your application code
Use dependency injection to get Hadoop *out* of your application codeUse dependency injection to get Hadoop *out* of your application code
Use dependency injection to get Hadoop *out* of your application code
 
Big data analytic platform
Big data analytic platformBig data analytic platform
Big data analytic platform
 

Andere mochten auch

T3 marketing automation and big data
T3 marketing automation and big dataT3 marketing automation and big data
T3 marketing automation and big dataPeter O'Kelly
 
Gilbane Boston 2012 Big Data 101
Gilbane Boston 2012 Big Data 101Gilbane Boston 2012 Big Data 101
Gilbane Boston 2012 Big Data 101Peter O'Kelly
 
Gilbane Boston 2012: XML and SQL: Not Dead Yet
Gilbane Boston 2012: XML and SQL: Not Dead YetGilbane Boston 2012: XML and SQL: Not Dead Yet
Gilbane Boston 2012: XML and SQL: Not Dead YetPeter O'Kelly
 
Gilbane Boston 2011 big data
Gilbane Boston 2011 big dataGilbane Boston 2011 big data
Gilbane Boston 2011 big dataPeter O'Kelly
 
201407 MIT CDO IQ conceptual data modeling, big data, and information quality
201407 MIT CDO IQ conceptual data modeling, big data, and information quality201407 MIT CDO IQ conceptual data modeling, big data, and information quality
201407 MIT CDO IQ conceptual data modeling, big data, and information qualityPeter O'Kelly
 
Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...
Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...
Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...Peter O'Kelly
 

Andere mochten auch (6)

T3 marketing automation and big data
T3 marketing automation and big dataT3 marketing automation and big data
T3 marketing automation and big data
 
Gilbane Boston 2012 Big Data 101
Gilbane Boston 2012 Big Data 101Gilbane Boston 2012 Big Data 101
Gilbane Boston 2012 Big Data 101
 
Gilbane Boston 2012: XML and SQL: Not Dead Yet
Gilbane Boston 2012: XML and SQL: Not Dead YetGilbane Boston 2012: XML and SQL: Not Dead Yet
Gilbane Boston 2012: XML and SQL: Not Dead Yet
 
Gilbane Boston 2011 big data
Gilbane Boston 2011 big dataGilbane Boston 2011 big data
Gilbane Boston 2011 big data
 
201407 MIT CDO IQ conceptual data modeling, big data, and information quality
201407 MIT CDO IQ conceptual data modeling, big data, and information quality201407 MIT CDO IQ conceptual data modeling, big data, and information quality
201407 MIT CDO IQ conceptual data modeling, big data, and information quality
 
Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...
Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...
Glibane 2016: How Consumer Cloud Conquered Corporate Control of Communication...
 

Ähnlich wie MLUC 2011 XQuery Enigma

Modeling TOGAF with ArchiMate
Modeling TOGAF with ArchiMateModeling TOGAF with ArchiMate
Modeling TOGAF with ArchiMateIver Band
 
The Outlook is Cloudy
The Outlook is CloudyThe Outlook is Cloudy
The Outlook is CloudyEduserv
 
Missing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscapMissing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscapStuart Weibel
 
Promoting the Semantic Web
Promoting the Semantic WebPromoting the Semantic Web
Promoting the Semantic WebOptum
 
An introduction to repository reference models
An introduction to repository reference modelsAn introduction to repository reference models
An introduction to repository reference modelsJulie Allinson
 
Openess and Portfolio Technology
Openess and Portfolio TechnologyOpeness and Portfolio Technology
Openess and Portfolio Technologydcambrid
 
Open lw reference architecture project
Open lw reference architecture projectOpen lw reference architecture project
Open lw reference architecture projectEric Kluijfhout
 
Adoption of Digital Learning Objects
Adoption of Digital Learning ObjectsAdoption of Digital Learning Objects
Adoption of Digital Learning ObjectsShalin Hai-Jew
 
Linked Open Data : opportunités et défis par Makx Dekkers
Linked Open Data : opportunités et défis par Makx DekkersLinked Open Data : opportunités et défis par Makx Dekkers
Linked Open Data : opportunités et défis par Makx DekkersABES
 
Darin McBeath XML Holland
Darin McBeath XML HollandDarin McBeath XML Holland
Darin McBeath XML HollandDave Kellogg
 
OLE Project - CULS Presentation
OLE Project - CULS PresentationOLE Project - CULS Presentation
OLE Project - CULS PresentationBeth Warner
 
W3C Library Linked Data Incubator Group - 2011
W3C Library Linked Data Incubator Group  - 2011W3C Library Linked Data Incubator Group  - 2011
W3C Library Linked Data Incubator Group - 2011Antoine Isaac
 
Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...
Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...
Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...DataWorks Summit/Hadoop Summit
 
Data Science Lecture: Overview and Information Collateral
Data Science Lecture: Overview and Information CollateralData Science Lecture: Overview and Information Collateral
Data Science Lecture: Overview and Information CollateralFrank Kienle
 
Resource Description Framework Approach to Data Publication and Federation
Resource Description Framework Approach to Data Publication and FederationResource Description Framework Approach to Data Publication and Federation
Resource Description Framework Approach to Data Publication and FederationPistoia Alliance
 
LOR Characteristics and Considerations
LOR Characteristics and ConsiderationsLOR Characteristics and Considerations
LOR Characteristics and ConsiderationsScott Leslie
 

Ähnlich wie MLUC 2011 XQuery Enigma (20)

Modeling TOGAF with ArchiMate
Modeling TOGAF with ArchiMateModeling TOGAF with ArchiMate
Modeling TOGAF with ArchiMate
 
The Outlook is Cloudy
The Outlook is CloudyThe Outlook is Cloudy
The Outlook is Cloudy
 
Missing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscapMissing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscap
 
Promoting the Semantic Web
Promoting the Semantic WebPromoting the Semantic Web
Promoting the Semantic Web
 
chrissy burns
chrissy burnschrissy burns
chrissy burns
 
chrissy burns
chrissy burnschrissy burns
chrissy burns
 
An introduction to repository reference models
An introduction to repository reference modelsAn introduction to repository reference models
An introduction to repository reference models
 
Openess and Portfolio Technology
Openess and Portfolio TechnologyOpeness and Portfolio Technology
Openess and Portfolio Technology
 
Open lw reference architecture project
Open lw reference architecture projectOpen lw reference architecture project
Open lw reference architecture project
 
Adoption of Digital Learning Objects
Adoption of Digital Learning ObjectsAdoption of Digital Learning Objects
Adoption of Digital Learning Objects
 
Linked Open Data : opportunités et défis par Makx Dekkers
Linked Open Data : opportunités et défis par Makx DekkersLinked Open Data : opportunités et défis par Makx Dekkers
Linked Open Data : opportunités et défis par Makx Dekkers
 
Darin McBeath XML Holland
Darin McBeath XML HollandDarin McBeath XML Holland
Darin McBeath XML Holland
 
Data-X-v3.1
Data-X-v3.1Data-X-v3.1
Data-X-v3.1
 
OLE Project - CULS Presentation
OLE Project - CULS PresentationOLE Project - CULS Presentation
OLE Project - CULS Presentation
 
W3C Library Linked Data Incubator Group - 2011
W3C Library Linked Data Incubator Group  - 2011W3C Library Linked Data Incubator Group  - 2011
W3C Library Linked Data Incubator Group - 2011
 
Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...
Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...
Implementing the Business Catalog in the Modern Enterprise: Bridging Traditio...
 
Data Science Lecture: Overview and Information Collateral
Data Science Lecture: Overview and Information CollateralData Science Lecture: Overview and Information Collateral
Data Science Lecture: Overview and Information Collateral
 
Resource Description Framework Approach to Data Publication and Federation
Resource Description Framework Approach to Data Publication and FederationResource Description Framework Approach to Data Publication and Federation
Resource Description Framework Approach to Data Publication and Federation
 
LOR Characteristics and Considerations
LOR Characteristics and ConsiderationsLOR Characteristics and Considerations
LOR Characteristics and Considerations
 
Data-X-Sparse-v2
Data-X-Sparse-v2Data-X-Sparse-v2
Data-X-Sparse-v2
 

Kürzlich hochgeladen

[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersThousandEyes
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 

Kürzlich hochgeladen (20)

[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for PartnersEnhancing Worker Digital Experience: A Hands-on Workshop for Partners
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 

MLUC 2011 XQuery Enigma

  • 1. XQuery’s Enigmatic Information Architecture Role MarkLogic User Conference 2011 Peter O’Kelly peter@okellyassociates.com
  • 2. Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 2
  • 3. Background Where I’m coming from Industry analyst/consultant working in information management and collaboration domains for ~30 years Background Application developer and data architect Product management and strategy roles at Lotus, IBM, Groove Networks, Macromedia, and Microsoft Industry analyst/consultant with the Patricia Seybold Group and Burton Group pbokelly.blogspot.com 4/28/2011 © 2011 O’Kelly Associates 3
  • 4. Background My high-level XQuery perspective XQuery truly is awesome… A very well-designed language and standards initiative, optimized for un- or semi-structured information But XQuery appears to be somewhat stalled, in terms of overall market momentum It’s important to understand and address the reasons for the stall Because a vibrant XQuery standard, along with related techniques and tools, are important for the evolution of information management 4/28/2011 © 2011 O’Kelly Associates 4
  • 5. Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 5
  • 6. Why XQuery is Awesome A purpose-built XML content manipulation language Gracefully applying the joy of sets to XML content Offering a sustainably complementary fit with SQL Designed by experts including SQL co-author Don Chamberlin Evolving to go far beyond queries With search, conditional expressions, function libraries, and more Can replace a kitchen sink of earlier technologies Fewer moving parts means more simplicity and less maintenance A W3C Recommendation, building on XML Schema, XPath, and other standards 4/28/2011 © 2011 O’Kelly Associates 6
  • 7.
  • 8. Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 8
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14. Other Evidence of Non-Mainstreaming Vendor uncertainty or other hesitation E.g., at Gilbane Boston 2010, few of the exhibitors I spoke with had even heard of XQuery Not a statistically significant survey, but still surprising Few of the current market-leading collaboration/ content platforms are based on XQuery Tangent: this suggests there is a compelling market opportunity for new collaboration/content entrants that are XQuery-based 4/28/2011 © 2011 O’Kelly Associates 14
  • 15. Exploring the XQuery Enigma Some issues that have probably limited XQuery market momentum Lack of a big-picture framework Installed base inertia Standards and politics The Internet ethos Limited techniques and tools [Don’t panic! We’ll return to the future-optimistic themes in a few minutes...] 4/28/2011 © 2011 O’Kelly Associates 15
  • 16. A Big-picture Framework A digital information item dichotomy Resources Digital artifacts optimized for human comprehension Organized in terms of narrative, hierarchy, and sequence Examples: books, magazines, documents (e.g., PDF, Word), Web pages, XBRL documents… Relations Application-independent descriptions of real-world things and relationships Examples: business domain databases, e.g., customer, sales, HR… 4/28/2011 © 2011 O’Kelly Associates 16
  • 17. The Resource/Relation Continuum 4/28/2011 © 2011 O’Kelly Associates 17 PDF docs XBRL docs Word docs DITA docs Desktop db Streaming db Operational db
  • 18. A Big-picture Framework Complementary levels of modeling abstraction Conceptual Technology-neutral Used to establish contextual consensus Also very useful, when done well, for creating logical models Logical Captures conceptual models in a technology rendering Examples: (beyond-the-basics) hypertext and relational Information workers and app developers ideally work at this level of abstraction Physical Includes implementation-level details Ideally, activity at this level is limited to system architects and administrators 4/28/2011 © 2011 O’Kelly Associates 18
  • 19. Conceptual Model Examples 4/28/2011 © 2011 O’Kelly Associates 19
  • 20. A Big-picture Framework 4/28/2011 © 2011 O’Kelly Associates 20
  • 21. The Lack of a Big-picture Framework Without a framework, there’s likely to be Uncertainty about what to use when Conflict based more on miscommunication and/or misunderstanding than real issues Insufficient focus on Application/data independence Conceptual/logical/physical model independence Low probability of appreciation for the sustainable and complementary fit between XQuery and SQL 4/28/2011 © 2011 O’Kelly Associates 21
  • 22. Installed Base Inertia Incumbent vendors DBMS vendors Application vendors Large organizations usually have distinct “content” and “data” management groups, often with little collaboration between them Content-focused people are often more instance-oriented and care a lot about schema flexibility Database-focused people are generally more type-oriented and care a lot about schema precision 4/28/2011 © 2011 O’Kelly Associates 22
  • 23. A Content-centric View 4/28/2011 © 2011 O’Kelly Associates 23
  • 24. A Database-centric View 4/28/2011 © 2011 O’Kelly Associates 24
  • 25. Installed Base Inertia Programmer preferences can be pernicious Object-oriented frameworks have a lot in common with resources (e.g., hierarchy, sequence, and positional navigation) The object/relational “impedance mismatch” is still irksome, in some tools/frameworks But that does not mean it’s reasonable to default to resource-oriented approaches for all domains, even if the application is XML-centric, because not all XML content is resource-centric Doing so can dumb-down DBMS usage patterns, with significant consequences 4/28/2011 © 2011 O’Kelly Associates 25
  • 26. Standards and Politics “The nice thing about standards is that you have so many to choose from” Andrew Tanenbaum As in the development of SQL, there are complex challenges at the intersection of standards groups, vendor agendas, and academic priorities The Open XML/ODF debate is another recent, relevant, and revealing case study 4/28/2011 © 2011 O’Kelly Associates 26
  • 27. Standards and Politics NoSQL “A rhetorically clever and manipulative name … Saying ‘NoSQL’ says what you’re against, not what you’re for” (Joe Maguire) As with the largely failed “object database” wave 20+ years ago, NoSQL extremists appear to underestimate the expressive power and utility of what they propose to displace While there is ample room for database-related innovation, polarizing the debate is unhelpful 4/28/2011 © 2011 O’Kelly Associates 27
  • 28. The Internet Ethos Lots to like Open, community-driven, vendor-independent… But also some risks; e.g., the Internet Doesn’t complain if your system is inefficient or ineffective Is culturally conducive to cyber-polarization E.g., there are probably still lively Internet forum debates about the relative merits of DTD, Schematron, RNG, and XML Schema And xBASE versus SQL, and RPG versus COBOL… This creates a key challenge: it’s difficult to get vitality readings on standards and technology alternatives Including major initiatives such as XQuery and XHTML 2.0 4/28/2011 © 2011 O’Kelly Associates 28
  • 29. Limited Techniques and Tools Some SQL reality checks Relatively few people work directly with SQL The vast majority of information workers and developers who benefit from using SQL do so indirectly, through tools ranging from IDEs to query/reporting applications The development of ODBC was pivotal for software vendors and application developers working with RDBMSs Making it possible for them to use a single interface model for multiple products 4/28/2011 © 2011 O’Kelly Associates 29
  • 30. Limited Techniques and Tools XQuery's market uptake has been constrained by the small number of XQuery-based tools and applications Which is in turn limited in part by the lack of a successful ODBC equivalent for XQuery Which, in turn, is partly a function of Microsoft’s apparent XQuery ambivalence Many XML-focused developers believe they get most of what they need from XPath Without tools to promote effective use of XQuery, it’s a difficult value proposition to make 4/28/2011 © 2011 O’Kelly Associates 30
  • 31. Limited Techniques and Tools Modeling techniques and tools are also pivotal There are some good options today for physical database modeling But few choices for logical modeling And almost a complete lack of conceptual modeling tools For XML information modeling, there are even fewer modeling technique/tool options today It’s also a cultural and incentive system challenge If developers are paid to primarily focus on physical models, that’s what most of them will do 4/28/2011 © 2011 O’Kelly Associates 31
  • 32. Limited Techniques and Tools Many XML-focused developers appear to believe they don’t need to invest time and attention in modeling In part because XML-focused application development often starts with existing XML schemas and/or documents rather than “green field” modeling But modeling is equally applicable to resource and relation domains, for Establishing contextual consensus Helping to promote Application/information independence Conceptual/logical/physical model independence Fostering the effective application of set theory and maximizing the use of declarative expressions 4/28/2011 © 2011 O’Kelly Associates 32
  • 33. Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 33
  • 34. Projections and Recommendations XQuery is going to be a mainstream success RDBMSs aren’t going away anytime soon The standards scene is evolving in subtly significant ways More and better modeling MarkLogic is very well positioned 4/28/2011 © 2011 O’Kelly Associates 34
  • 35. XQuery Will be a Mainstream Success And already is a success, for many progressive IT organizations and software vendors The next wave of XQuery momentum will likely come more from content management than traditional database management Providing significant opportunities to have fewer information architecture moving parts E.g., to spend less on specialized enterprise content management, records management, and Web content management servers and tools 4/28/2011 © 2011 O’Kelly Associates 35
  • 36. XQuery Will be a Mainstream Success Recommendations Learn and fully leverage XQuery Go beyond the basics to master the full XQuery language “Querying XML,” by Jim Melton and Stephen Buxton, is a useful resource in this context Seek to simplify and consolidate, e.g., To do less scripting/programming and more declarative development using XQuery To migrate content and apps from legacy ECM systems 4/28/2011 © 2011 O’Kelly Associates 36
  • 37. RDBMSs Aren’t Going Away Resources and relations are complementary And XQuery and SQL offer very strong synergy Systems such as Google’s Megastore are important leading indicators, as hybrid models “NoSQL” will rapidly evolve Initially implied “Just say ‘no’ to SQL” Later quietly redefined as “Not Only SQL” What may be next: “New Opportunities for SQL” I.e., some developers may reconsider the value of SQL and RDBMSs, after hitting NoSQL limitations 4/28/2011 © 2011 O’Kelly Associates 37
  • 38. RDBMSs Aren’t Going Away Recommendations Develop expertise in both (beyond-the-basics) hypertext and relational models And explore the information flows between them Provide clear customer requirements and feedback to your RDBMS, application, and tool vendors Encourage them to fully exploit resource/relation synergy Establish clear developer criteria on what to use when, e.g., for NoSQL alternatives Consider applying the framework presented earlier 4/28/2011 © 2011 O’Kelly Associates 38
  • 39. Subtly Significant Standards Evolution The industry is a very different place compared to when SQL was standardized in the mid-1980s The Internet ethos is pervasive, and key vendors have learned to productively play the standards game together There have been some major standards changes recently, e.g., the discontinuation of XHTML 2.0 But there is also clear market momentum consolidation around standards including XML Schema, XPath 2.0, XSLT, and HTML5 And, although not always obviously, XQuery 4/28/2011 © 2011 O’Kelly Associates 39
  • 40. Subtly Significant Standards Evolution Recommendations Place well-informed standards bets, regularly check assumptions, and be willing to make course corrections Get involved Make your standards-related requirements clear to your strategic vendors Actively participate in standards activities 4/28/2011 © 2011 O’Kelly Associates 40
  • 41. More and Better Modeling Conceptual, logical, and physical modeling are critical success factors for both resources and relations Organizations that under-invest in modeling are essentially reverting to the obsolete programs-have-files approach, limiting Application/data (and content) independence Conceptual/logical/physical model independence 4/28/2011 © 2011 O’Kelly Associates 41
  • 42. More and Better Modeling Recommendations Develop modeling expertise Explore resources such as “Mastering Data Modeling” (Carlis/Maguire) Apply the big-picture framework for consensus on (resources + relations) * (conceptual/logical/physical) Build and consistently use model repositories Also ensure modeling and reuse are supported by developer incentive systems Provide clear modeling-related requirements to your tool and server vendors 4/28/2011 © 2011 O’Kelly Associates 42
  • 43. MarkLogic is Very Well Positioned MarkLogic Placed an early bet on XQuery, and continued to focus on XQuery while many other vendors balked Has insights from XML information management market leadership in key domains including media, government, and finance Is led by a deeply experienced and strong team Recommendations Share your experiences this week and consider proposing a customer case study for MLUC 2012 4/28/2011 © 2011 O’Kelly Associates 43
  • 44. Agenda Background Why XQuery is awesome The XQuery enigma: why it’s not yet mainstream Projections and recommendations Q&A 4/28/2011 © 2011 O’Kelly Associates 44

Hinweis der Redaktion

  1. The W3C’s take on why XQuery is awesome Captured 20110321
  2. Why this image is included: I was confident XQuery was about to have a major market impact several years ago; why is it taking so long?...
  3. Search snapshot on 20110321, excluding Burton Group contentA Gartner search for “NoSQL” returned 11 resultsSimilar overall results with a Forrester search – 31 document hits for XQuery; 799 for SQLReturned 73 results on search when expanded to include all Gartner content – i.e., including Burton Group content; the vast majority of Gartner content referencing XQuery is in Burton Group documents I either personally wrote or influenced
  4. Captured 20110321Point of this slide: checking mainstream tech instead of subscription-based analyst firms, there’s a similar result – a surprising shortage of XQuery news coverage
  5. Captured 20110322A similar search comparing SQL and XQuery makes the latter, relatively, look like it’s flat-lining (is barely discernible)Google Trends is also a useful service, if you want to explore further
  6. Search done on 20110321 for 200101 – 201004
  7. On collab/content – e.g., IBM Notes/Domino, Connections, FileNet; Microsoft SharePoint
  8. Not an exhaustive list
  9. This is a high-level dichotomy – and not meant to be precise or mutually-exclusive (i.e., some info items have both resource and relation attributes)
  10. This is meant to be illustrative – neither precise nor exhaustive
  11. Point of this slide: reinforce ability to discern major similarities/differences between two tools/services focused on similar domain, by comparing/contrasting model diagrams Non-technical people can easily learn how to read/use this type of model – not so with most logical and physical model diagramming techniquesEvernote conceptual model fragment example from http://www.quepublishing.com/articles/article.aspx?p=1684320 Incomplete – a full conceptual model includes accompanying documentation, e.g., with entity definitions and examplesMicrosoft OneNote 2010 conceptual model fragment example from http://www.quepublishing.com/articles/article.aspx?p=1684320 Reason for including it: it provides an example, comparing it to the Evernote conceptual model fragment, of how easy it is to understand domains, when using conceptual models – e.g., the fact that OneNote has a more elaborate info item containment structure, and supports tags at the item/paragraph level, while Evernote tagging is at the note/page level. That’s not meant to be a judgment call; the extent to which Evernote or OneNote is more useful is a function of your info item/note-taking needs.
  12. Point of having a merged cell for physical: it’s all coming together – it’s increasingly difficult to distinguish the underlying physical model services…Here again, hypertext is not 1:1 with HTML – it’s beyond-the-basics hypertext as manifested, e.g., in Web publishing and collaboration-oriented systems/servers
  13. Content/document management view: I don’t need relational, and it’s too restrictive
  14. Database management view of resources: a shrinking info anomalyConsidering these sometimes polarized views, it’s not surprising XQuery often doesn’t find a receptive audience
  15. Altova and Embarcadero are two vendors to explore in this context
  16. Lack of robustly useful and popularconceptual modeling tools is a very big problem
  17. Aside: same is often true to for SQL developers, with similarly unfortunate consequences
  18. Note: challenges will often be more political/cultural than technical
  19. O’Kelly Associates can help with this domain 
  20. O’Kelly Associates can help with this domain 