Related papers: Popularity Ranking of Database Management Systems
This study aims to inspect and evaluate the integration of database queries and their use in e-commerce product searches. It has been observed that e-commerce is one of the most prominent trends, which have been emerged in the business…
A data store allows application processes to put and get data from a shared memory. In general, a data store cannot be modelled as a strictly sequential process. Applications observe non-sequential behaviours, called anomalies. The set of…
At DBKDA 2019, we demonstrated that StrongDBMS with simple but rigorous optimistic algorithms, provides better performance in situations of high concurrency than major commercial database management systems (DBMS). The demonstration was…
Recommender systems have become increasingly important with the rise of the web as a medium for electronic and business transactions. One of the key drivers of this technology is the ease with which users can provide feedback about their…
Big Data is defined as high volume of variety of data with an exponential data growth rate. Data are amalgamated to generate revenue, which results a large data silo. Data are the oils of modern IT industries. Therefore, the data are…
The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity…
With the wide application of time series databases (TSDBs) in big data fields like cluster monitoring and industrial IoT, there have been developed a number of TSDBs for time series data management. Different TSDBs have test reports…
Big Data technology is described. Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. There is constructed dataspace architecture. Dataspace has focused solely - and…
Traditional database systems are built around the query-at-a-time model. This approach tries to optimize performance in a best-effort way. Unfortunately, best effort is not good enough for many modern applications. These applications…
This article presents an empirical study of how the use of relational database access technologies in open source Java projects evolves over time. Our observations may be useful to project managers to make more informed decisions on which…
In-database machine learning has been very popular, almost being a cliche. However, can we do it the other way around? In this work, we say "yes" by applying plain old SQL to deep learning, in a sense implementing deep learning algorithms…
The digital transformation of companies has led to the evolution of databases towards Big Data. Our work is part of this context and concerns more particularly the mechanisms to extract datasets stored in a Data Lake and to store the data…
Containers, enabling lightweight environment and performance isolation, fast and flexible deployment, and fine-grained resource sharing, have gained popularity in better application management and deployment in addition to hardware…
Graphs have become the best way we know of representing knowledge. The computing community has investigated and developed the support for managing graphs by means of digital technology. Graph databases and knowledge graphs surface as the…
In this paper, we proposed a new technique for backing up and restoring different Database Management Systems (DBMS). The technique is enabling to backup and restore a part of or the whole database using a unified interface using ASP.NET…
In today's world data is being generated at a high rate due to which it has become inevitable to analyze and quickly get results from this data. Most of the relational databases primarily support SQL querying with a limited support for…
The last years have seen a growing interest in collaborative systems like electronic marketplaces and P2P file sharing systems where people are intended to interact with other people. Those systems, however, are subject to security and…
Vector database management systems (VDBMSs) play a crucial role in facilitating semantic similarity searches over high-dimensional embeddings from diverse data sources. While VDBMSs are widely used in applications such as recommendation,…
Relational Database Management Systems designed for Online Analytical Processing (RDBMS-OLAP) have been foundational to democratizing data and enabling analytical use cases such as business intelligence and reporting for many years.…
This paper discusses a method for implementing a probabilistic inference system based on an extended relational data model. This model provides a unified approach for a variety of applications such as dynamic programming, solving sparse…