Data lakes are becoming increasingly prevalent for Big Data management and data
analytics. In contrast to traditional 'schema-on-write'approaches such as data warehouses …

This paper evaluates the suitability of Apache Arrow, Parquet, and ORC as formats for
subsumption in an analytical DBMS. We systematically identify and explore the high-level …

Efficient big data management is a dire necessity to manage the exponential growth in data
generated by digital information systems to produce usable knowledge. Structured …

Over the past several decades, the amount of data being stored and analyzed has increased
exponentially. Businesses across industries and sectors have begun relying on this data to …

In the context of data analytics, so-called lakehouses refer to novel variants of data platforms
that attempt to combine characteristics of data warehouses and data lakes. In this way …

Quantum computing has emerged as a promising tool for transforming the landscape of
computing technology. Recent efforts have applied quantum techniques to classical …

Data processing engines increasingly leverage distributed file systems for scalable, cost-
effective storage. While the Apache Parquet columnar format has become a popular choice …

Purpose This paper aims to address the pressing challenges in research data management
within institutional repositories, focusing on the escalating volume, heterogeneity and multi …

The digital shift in society is making continuous growth of data. However, choosing a
suitable storage architecture to efficiently store, process, and manage data from numerous …

Managing unstructured and heterogeneous data, integrating them, and enabling their
analysis are among the key challenges in data ecosystems, together with the need to …