[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84192-en":3,"doc-seo-84192-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},84192,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Benchmark Engineering as a Design Instrument for Heterogeneous Information Systems","Contemporary information systems run over heterogeneous, continuously evolving data environments where representation and structural redesign choices shape system behavior. Existing benchmarking methods largely assume static datasets and fixed schemas, limiting analysis of architectural trade-offs and evolution in multi-model settings. The paper proposes TransforMMer, a framework for evolution-aware, representation-aware benchmark engineering that derives structure from raw data and generates comparable relational, document, and graph benchmark variants with reproducible transformations.","arXiv :2607 .07 175v 1 [ cs .DB] 8 Jul 2026  \nBenchmark Engineering as a Design Instrument for Heterogeneous Information Systems  \nJáchym Bártíka,∗, Alžběta Šrůtkováa , Irena Holubováa  \na Department of Software Engineering, Charles University, Malostranské nám. 25,  \nPraha 118 00, Czech Republic  \nAbstract  \nContemporary information systems operate in heterogeneous and continuously evolving data environments, where representation choices and structural redesign decisions strongly influence system behavior. Existing benchmarking approaches, however, rely mostly on static datasets and fixed schemas, providing limited support for analyzing architectural trade-offs or guiding evolution in multi-model settings.  \nThis paper introduces TransforMMer, a framework for evolution-aware and representation-aware benchmark engineering in heterogeneous information systems. The approach treats benchmark construction as a systematic design process: starting from raw data, inferring structure, refining it conceptually, and generating comparable dataset variants across relational, document, and graph systems. The framework is grounded in a unified representation that enables explicit modeling of schemas and cross-model mappingsand supports reproducible transformations across alternative representations.  \nWe position benchmarking as a system-design tool for evaluating architectural and representation-level decisions in evolving information systems, rather than as a static comparison of database engines. Through controlled benchmark construction scenarios on real-world datasets, we demonstrate how structural redesign steps—such as embedding, enrichment, and hybrid partitioning—affect observed query costs across systems. The results show that performance differences emerge primarily from the interaction between  \n∗ Corresponding author.  \nEmail addresses: [jachym.bartik@matfyz.cuni.cz](jachym.bartik@matfyz.cuni.cz) (Jáchym Bártík), [srutkova.alzbeta@gmail.com](srutkova.alzbeta@gmail.com) (Alžběta Šrůtková), [irena.holubova@matfyz.cuni.cz](irena.holubova@matfyz.cuni.cz)[ ](irena.holubova@matfyz.cuni.cz)(Irena Holubová)  \nworkload and representation design.  \nBy enabling systematic generation of structurally distinct yet semantically aligned dataset variants, the proposed approach connects conceptual data modeling with empirical system evaluation and supports reproducible, evolution-aware analysis of heterogeneous information systems. Keywords: multi-model data management, benchmark engineering, schema evolution, heterogeneous information systems, cross-model transformation, reproducible benchmarking  \n1. Introduction and Motivation  \nThe emergence of Big Data has significantly changed the landscape of modern information systems. Contemporary applications increasingly operate over heterogeneous data environments that combine relational, document, key-value, and graph data models. This diversity has led to the development of multi-model database systems (MMDBs), which integrate different data abstractions within a single platform and support a broad spectrum of workloads.  \nWhile multi-model systems improve flexibility and enable model-specific optimizations, they also introduce substantial complexity. Differences in schema structures, storage strategies, indexing mechanisms, and query languages complicate both system design and evaluation. This challenge becomes even more pronounced in environments where schemas evolve overtime, data representations change, and systems integrate multiple storage technologies. As a result, systematic evaluation of heterogeneous information systems remains difficult.  \nBenchmarking has traditionally served as a primary method for evaluating database systems and data processing platforms. Established benchmarks, such as TPC [1] for relational systems, LDBC [2] for graph databases, and YCSB [3] for key-value stores, enable controlled, reproducible experiments. However, these benchmarks typically assume fixed schemas, s","cbCaigGNCOI7xZTF","https://ap.wps.com/l/cbCaigGNCOI7xZTF","pdf",3490762,4,1,54,"English","en",105,"# Abstract\n# Introduction and Motivation","[{\"question\":\"What limitation do existing benchmarking approaches have in heterogeneous information systems?\",\"answer\":\"They mostly rely on static datasets and fixed schemas, which makes it difficult to analyze architectural trade-offs or guide evolution across multi-model settings.\"},{\"question\":\"What is TransforMMer, and what problem does it address?\",\"answer\":\"TransforMMer is a framework for evolution-aware and representation-aware benchmark engineering. It treats benchmark construction as a design process that infers and refines structure and generates comparable benchmark variants across relational, document, and graph systems.\"},{\"question\":\"How do the benchmark construction steps influence query cost in the paper’s experiments?\",\"answer\":\"Controlled scenarios show that structural redesign steps—such as embedding, enrichment, and hybrid partitioning—change observed query costs, with performance differences driven mainly by the interaction between workload and representation design.\"}]",1784193839,136,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"benchmark-engineering-as-a-design-instrument-for-heterogeneous-information-systems","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":20},"https://docshare.wps.com/document/benchmark-engineering-as-a-design-instrument-for-heterogeneous-information-systems/84192/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-27","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What limitation do existing benchmarking approaches have in heterogeneous information systems?","Question",{"text":75,"@type":76},"They mostly rely on static datasets and fixed schemas, which makes it difficult to analyze architectural trade-offs or guide evolution across multi-model settings.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is TransforMMer, and what problem does it address?",{"text":80,"@type":76},"TransforMMer is a framework for evolution-aware and representation-aware benchmark engineering. It treats benchmark construction as a design process that infers and refines structure and generates comparable benchmark variants across relational, document, and graph systems.",{"name":82,"@type":73,"acceptedAnswer":83},"How do the benchmark construction steps influence query cost in the paper’s experiments?",{"text":84,"@type":76},"Controlled scenarios show that structural redesign steps—such as embedding, enrichment, and hybrid partitioning—change observed query costs, with performance differences driven mainly by the interaction between workload and representation design.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]