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UDBMS: Road to Unification for Multi-model Data Management
[chapter]
2018
Msphere
Preserved Fulltext
One of the greatest challenges in big data management is the "Variety" of the data. The data may be presented in various types and formats: structured, semi-structured and unstructured. ...
In this paper, we envision novel principles and technologies to handle multiple models of data in one unified database system, including model-agnostic storage, unified query processing and indexes, in-memory ...
The existing results for query optimization and transaction model mainly work on a single model, either structured or semi-structured data. ...
doi:10.1007/978-3-030-01391-2_33
fatcat:wr63msuftjck3lvpnoa6y2r2g4
Schema Extraction on Semi-structured Data
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2012.08105v1 fatcat:p6542iwovjgullpiszhv45kuve
Schema extraction plays an important role in understanding schemas, optimizing queries, and validating data consistency. ...
With the continuous development of NoSQL databases, more and more developers choose to use semi-structured data for development and data management, which puts forward requirements for schema management ...
large-scale organization, storage and analysis of semi-structured data. ...
arXiv:2012.08105v2
fatcat:hco64wxnrfawrk3twlff2xia3i
A Decade of XML Data Management: An Industrial Experience Report from Oracle
2009
Proceedings / International Conference on Data Engineering
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and query optimisation techniques for different XML use cases. ...
We discuss the lessons learnt in supporting both data-centric and document-centric XMLDB applications within a single database system and the need for the implementation of different XML storage, index ...
With schema and non-schema based XML and universal structure, value, path and relational XMLTable indexing strategies for XML, there are many cost based choices to optimize the physical design of XML for ...
doi:10.1109/icde.2009.18
dblp:conf/icde/LiuM09
fatcat:oecsthn7q5g5bp2y3x7vbnoq5i
Towards a physical XML independent XQuery/SQL/XML engine
2008
Proceedings of the VLDB Endowment
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There are industrial efforts for building hybrid XQuery and SQL/XML engines that support both languages so that users can manage and query both relational and XML data on one platform. ...
with relational indexes, binary XML storage with schema agnostic path-value-order key XMLIndex, SQL/XML view over relational data and relational view over XML. ...
ACKNOWLEDGEMENTS We gratefully acknowledge the contributions of all the members of the Oracle XML DB development and product management teams. ...
doi:10.14778/1454159.1454177
fatcat:jdlyx66mcvhovhj67z7fy56q2a
The Snowflake Elastic Data Warehouse
2016
Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16
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Public cloud platforms now offer virtually unlimited compute and storage resources on demand. At the same time, the Software-as-a-Service (SaaS) model brings enterprise-class ...
We continue to improve and extend core query processing functionality, both for standard SQL and semi-relational extensions. ...
We are currently working on improving the data access performance by providing additional metadata structures and data re-organization tasks-with a focus on minimal to no user interaction. ...
doi:10.1145/2882903.2903741
dblp:conf/sigmod/DagevilleCZAABC16
fatcat:5ehnby2gvffujfsyboulqq2pxu
An LSM-based Tuple Compaction Framework for Apache AsterixDB (Extended Version)
[article]
2020
arXiv
pre-print
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Our focus in this paper is to address the storage overhead issue by introducing a tuple compactor framework that infers and extracts the schema from self-describing semi-structured records during the data ...
We have implemented and empirically evaluated our approach to measure its impact on storage, data ingestion, and query performance in the context of Apache AsterixDB. ...
It was also supported by NSF awards IIS-1838248 and CNS-1925610, industrial support from Amazon, Google, Microsoft and Couchbase, and the Donald Bren Foundation (via a Bren Chair). ...
arXiv:1910.08185v2
fatcat:dktqsj47i5gbrn4xyoc2aullt4
A COMPARATIVE STUDY AMONG THE MAIN CATEGORIES OF NoSQL DATABASES
2020
Al-Azhar Bulletin of Science
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Relational databases are usually used for data storage and retrieval. They are suitable for limited data volume. ...
But when it comes to Bigdata, we need to use more flexible databases that satisfy the need to handle semi-structured and unstructured data. These databases are called NoSQL (Not only SQL) databases. ...
Graph databases are schema-free and come up with efficient storage of semi-structured and unstructured data [15, 29] . ...
doi:10.21608/absb.2020.210374
fatcat:umexpeuv3veo3o5ihqhn3pcvjq
Analysis and Evaluation of Techniques for Managing Unstructured and Semi-Structured Data in a MapReduce Platform
2017
International Journal Of Engineering And Computer Science
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Since, almost most kinds of database systems are designed to manage well-structured data requiring users to design a schema before storing and querying data. ...
Having a single data platform for managing both well-structured data, unstructured and semi-structured data is beneficial to users; this approach reduces significantly integration, migration, development ...
The schema based on structured data may have bounded dimensions with unlimited number of elements as formal schema definition, while, schema based on unstructured and semi-structured data has unlimited ...
doi:10.18535/ijecs/v6i2.03
fatcat:qonsrnvrtng4fkzvqqluwcqft4
Comparative of Mediator Approach for Database Integration
2015
Journal of Computer Science
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Six applications which are based on mediator approach have ...
Acknowledgment The researchers would like to thank Universiti Sultan Zainal Abidin for providing facilities and services to do this research. ...
Ethics This article is original and contains unpublished material. The corresponding author confirms that all of the other authors have read and approved the manuscript and no ethical issues involved. ...
doi:10.3844/jcssp.2015.204.217
fatcat:v3xwfbhyvzfjno33l63qt3aafe
Managing XML Data to optimize Performance into Object-Relational Databases
2011
Database Systems Journal
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It is detailed the possibility of storing XML data into such databases, using for exemplification an Oracle database and there are tested some optimizing techniques of the queries over XMLType tables, ...
This paper propose some possibilities for manage XML data in order to optimize performance into object-relational databases. ...
: adapted from [12])
CHARACTERISTIC
STRUCTURED STORAGE
LOB STORAGE
Database schema flexibility
Limited flexibility for schema
changes
Good flexibility for schema
changes
Data integrity and ...
doaj:237a7f5a3b404277bc90170b0aa207ea
fatcat:lr6u4q4exzhutjjdqcme3ltjzy
Database storage management with object-based storage devices
2005
Proceedings of the 1st international workshop on Data management on new hardware - DAMON '05
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of schema and disk parameters yields 2D placement
2D data structure access
• On-disk storage requires serialization
• Access along one dimension is efficient
-i.e., sequential
• Records
Attributes ...
Create object for relation
2. Attach schema attribute
3. ...
Solving the "parameter problem" • Relying on storage vendors to expose parameters is problematic -Measuring parameters is difficult and fragile (but not impossible) • ...
doi:10.1145/1114252.1114264
fatcat:utjwsoww75fknhsl5mrdjzjg4e
ClothoDecoupling Memory Page Layout from Storage Organization
[chapter]
2004
Proceedings 2004 VLDB Conference
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Clotho creates in-memory pages individually tailored for compound and dynamically changing workloads, and enables efficient use of different storage technologies (e.g., disk arrays or MEMS-based storage ...
Existing techniques, however, do not optimize accesses to all levels of the memory hierarchy and for all the different workloads, because each storage level uses different technology (cache, memory, disks ...
Logic, Microsoft, Network Appliance, Oracle, Panasas, Seagate, Sun, and Veritas) for their interest, insights, feedback, and support. ...
doi:10.1016/b978-012088469-8/50062-0
fatcat:gcez3b6dfjentmf7d3ev3j23si
Handling Evolution in Big Data Architectures
2020
Baltic Journal of Modern Computing
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In this paper, we analyze architectures designed for Big Data processing and analysis described in the literature with the purpose to identify the most appropriate solution for the evolution problem. ...
Data processing and analysis. ...
Hive is used for the storage of structured source data and Kafka is used for log file data. OLAP analysis is provided by Kylin for precalculated cube data and Impala for ad-hoc queries. ...
doi:10.22364/bjmc.2020.8.1.02
fatcat:ghvrfrud7rcblj7a3ww3pzn2dm
UDBMS: Road to Unification for Multi-model Data Management
[article]
2016
arXiv
pre-print
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For example, semi-structured, graph and relational models are examples of data models that may be supported by a new system. ...
UDBMS will provide several new features such as unified data model and flexible schema, unified query processing, unified index structure and cross-model transaction guarantees. ...
Flexible schema management. Original ORDBMS assumes the perfect schema based world. Semi-structure data and unstructured data challenges ORDBMS with schema-less design. ...
arXiv:1612.08050v1
fatcat:7qek5sljnrbjvhuwpfsh4duj5y
JSON data management
2014
Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14
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This SQL/JSON approach offers significant benefits to application developers as they can use one product to manage both relational data and semi-structured flexible schema data. ...
JSON is a light-weight and flexible semi-structured data format supporting constructs common in most programming languages. ...
We thank Vikas Arora, Andrew Witkowski for management efforts of SQL/JSON development at Oracle. ...
doi:10.1145/2588555.2595628
dblp:conf/sigmod/LiuHM14
fatcat:rrf7sofrfvcdplcbrapk5rb4ji
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