Denormalizing data into schema-free databases

Vajk, Tamás; Fehér, Péter; Fekete, Krisztián; Charaf, Hassan

doi:10.1109/coginfocom.2013.6719198

Cited by 26 publications

(13 citation statements)

References 5 publications

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“…Other studies [5,6] have investigated the process of transforming relational databases into a NoSQL model. Li [5] have proposed an approach for transforming a relational database into HBase (column-oriented system).…”

Section: Introductionmentioning

confidence: 99%

“…Regarding the state of the art, some of the existing works [5,6] focus on relational model that, unlike UML class diagram, lacks of semantic richness, especially through the several types of relationships that exist between classes. Other solutions, [9,15] have the advantage to start from the conceptual level.…”

Section: Introductionmentioning

confidence: 99%

“…Li [5] have proposed an approach for transforming a relational database into HBase (column-oriented system). Vajk et al [6] defined a mapping from a relational model to document-oriented model using MongoDB.…”

Section: Introductionmentioning

confidence: 99%

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MDA-Based Approach for NoSQL Databases Modelling

Abdelhédi¹,

Brahim

Atigui

et al. 2017

Big Data Analytics and Knowledge Discovery

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract. It is widely accepted today that relational systems are not appropriate to handle Big Data. This has led to a new category of databases commonly known as NoSQL databases that were created in response to the needs for better scalability, higher flexibility and faster data access. These systems have proven their efficiency to store and query Big Data. Unfortunately, only few works have presented approaches to implement conceptual models describing Big Data in NoSQL systems. This paper proposes an automatic MDA-based approach that provides a set of transformations, formalized with the QVT language, to translate UML conceptual models into NoSQL models. In our approach, we build an intermediate logical model compatible with column, document and graph oriented systems. The advantage of using a unified logical model is that this model remains stable, even though the NoSQL system evolves over time which simplifies the transformation process and saves developers efforts and time.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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MDA-Based Approach for NoSQL Databases Modelling

Abdelhédi¹,

Brahim

Atigui

et al. 2017

Big Data Analytics and Knowledge Discovery

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“…In [14], the author proposed an approach for transforming a relational database into a column-oriented NoSQL database. In [18], the author studies "denormalizing" data into schema-free databases. However, these approaches never consider the conceptual model of data warehouses.…”

Section: State Of the Artmentioning

confidence: 99%

“…Nowadays, research attention has turned towards using these systems for storing "big" data and analyzing it. This work joins substantial ongoing work on the area on the use of NoSQL solutions for data warehousing [4,6,18,19]. In this paper, we focus on one class of NoSQL stores: columnoriented systems such as HBase [11] or Cassandra [13] and inspired by Bigtable [2].…”

Section: Introductionmentioning

confidence: 99%

Implementation of Multidimensional Databases in Column-Oriented NoSQL Systems

Chevalier

Malki

Kopliku

et al. 2015

Advances in Databases and Information Systems

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CONST: Continuous online NoSQL schema tuning

2020

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Self‐tuning is a feature of autonomic databases that includes the problem of automatic schema design. Automating the schema design process is critical to provide an optimized schema that increases the performance of an application's workload in NoSQL databases. There has been important work on automated design tuning for NoSQL databases. Existing solutions take an offline approach to the schema design problem and leave several important decisions to database administrators. Although offline approaches recommend good and efficient schemas, their analysis is far too heavy‐weight to be run continuously. This paper develops a novel self‐tuning control loop, called CONST, for online monitoring, analysis, and schema tuning a managed NoSQL database system that automatically modify the current schema design reacting to changes in the application's workload. CONST provides components that fulfill IBM's MAPE‐K loop phases to support self‐tuning. We describe an implementation of the proposed CONST loop on top of the Cassandra wide column store and evaluate its performance experimentally. Our results show the low overhead of CONST and demonstrate its ability to tune a schema design in response to changes in the application's workload.

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Denormalizing data into schema-free databases

Cited by 26 publications

References 5 publications

MDA-Based Approach for NoSQL Databases Modelling

MDA-Based Approach for NoSQL Databases Modelling

Implementation of Multidimensional Databases in Column-Oriented NoSQL Systems

CONST: Continuous online NoSQL schema tuning

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