Closing the functional and Performance Gap between SQL and NoSQL

Liu, Zhen Hua; Hammerschmidt, Beda Christoph; McMahon, Doug; Liu, Ying; Chang, Hui Joe

doi:10.1145/2882903.2903731

Cited by 32 publications

(26 citation statements)

References 12 publications

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“…Find a department D1's head and all individuals who report directly or indirectly to D1's head Assume the graph data stays in the underlying relational base tables T1, T2, shown in Figure 1. The two declarative graph PGQL queries (Property Graph Query Language, see specifications in [22]) in Table 2 are created on top of T1 and T2. Table 2 also shows equivalent SQL implementations using a recursive WITH clause.…”

Section: Equivalent Sql Querymentioning

confidence: 99%

Multi-model Database Management Systems - A Look Forward

Liu

Gawlick

et al. 2019

Heterogeneous Data Management, Polystores, and Analytics for Healthcare

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The existence of the variety of data models and their associated data processing technologies make data management extremely complex. In this paper, we envision a single Multi-Model DataBase Management Systems (MMDBMS) providing declarative accesses to a variety of data models. We briefly review the history of the evolution of the DBMS technology to derive requirements of MMDBMSs and then we illustrate our ideas of building MMDBMSs satisfying those requirements. Since the relational algebra is not powerful enough to provide a mathematical foundation for MMDBMSs, we promote the category theory as a new theoretical foundation, which is a generalization of the set theory. We also suggest a set of shared data infrastructure services among data models to support "Just-In-Time" multi-model data access autonomously.

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Section: Equivalent Sql Querymentioning

confidence: 99%

Multi-model Database Management Systems - A Look Forward

Liu

Gawlick

et al. 2019

Heterogeneous Data Management, Polystores, and Analytics for Healthcare

Self Cite

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“…Most solutions consider the mapping of JSON data to relational data. In this context, several RDBMS vendors support JSON data management, like Oracle [1,29], DB2 [30], SQL Server [31] and PostgreSQL [32]. Their capabilities usually include: (i) a binary storage format, like Oracle OSON and DB2 BSON; (ii) SQL extensions that allow the generation and retrieval of data in JSON format, like Oracle SQL/JSON; (iii) APIs to manipulate JSON data, like DB2 JSON API; and (iv) indexing strategies for JSON data.…”

Section: Survey Scope: What Is Outmentioning

confidence: 99%

When Relational-Based Applications Go to NoSQL Databases: A Survey

2019

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Several data-centric applications today produce and manipulate a large volume of data, the so-called Big Data. Traditional databases, in particular, relational databases, are not suitable for Big Data management. As a consequence, some approaches that allow the definition and manipulation of large relational data sets stored in NoSQL databases through an SQL interface have been proposed, focusing on scalability and availability. This paper presents a comparative analysis of these approaches based on an architectural classification that organizes them according to their system architectures. Our motivation is that wrapping is a relevant strategy for relational-based applications that intend to move relational data to NoSQL databases (usually maintained in the cloud). We also claim that this research area has some open issues, given that most approaches deal with only a subset of SQL operations or give support to specific target NoSQL databases. Our intention with this survey is, therefore, to contribute to the state-of-art in this research area and also provide a basis for choosing or even designing a relational-to-NoSQL data wrapping solution.

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“…In the first approach, they introduced the ability to store XML as a native type (Microsoft SQL Server 2005) [14], but its heavy format increased disk usage [17]. This decreases the functional and performance gap between SQL and NoSQL [9].…”

Section: Related Workmentioning

confidence: 99%

Model for Dynamic and Hierarchical Data Repository in Relational Database

Piech

Frącz

Turek

et al. 2018

csci

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The aim of this research is to build an open schema model for a digital sources repository in a relational database. This required us to develop a few advanced techniques. One of them was to keep and maintain a hierarchical data structure pushed into the repository. A second was to create constraints on any hierarchical level that allows for the enforcement of data integrity and consistency. The created solution is mainly based on a JSON file as a native column type, which was designed for holding open schema documents. In this paper, we present a model for any repository that uses hierarchical dynamic data. Additionally, we include a structure for normalizing the input and description for the data in order to keep all of the model assumptions. We compared our solution with a well-known open schema model-Entity-Attribute-Value-in the scope of saving data and querying about relationships and contents from the structure. The results show that we achieved improvements in both the performance and disk space usage, as we extended our model with a few new features that the previous model does not include. The techniques developed in this research can be applied in every domain where hierarchical dynamic data is required, as demonstrated by the digital book repository that we have presented.

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Closing the functional and Performance Gap between SQL and NoSQL

Cited by 32 publications

References 12 publications

Multi-model Database Management Systems - A Look Forward

Multi-model Database Management Systems - A Look Forward

When Relational-Based Applications Go to NoSQL Databases: A Survey

Model for Dynamic and Hierarchical Data Repository in Relational Database

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