Related papers: HTAP Databases: A Survey
Querying and exploring massive collections of data sources, such as data lakes, has been an essential research topic in the database community. Although many efforts have been paid in the field of data discovery and data integration in data…
Hyperproperties are commonly used in computer security to define information-flow policies and other requirements that reason about the relationship between multiple computations. In this paper, we study a novel class of hyperproperties…
Distributed Hash Tables (DHTs) have been used in several applications, but most DHTs have opted to solve lookups with multiple hops, to minimize bandwidth costs while sacrificing lookup latency. This paper presents D1HT, an original DHT…
As we reach exascale, production High Performance Computing (HPC) systems are increasing in complexity. These systems now comprise multiple heterogeneous computing components (CPUs and GPUs) utilized through diverse, often vendor-specific…
Array operations are one of the most concise ways of expressing common filtering and simple aggregation operations that is the hallmark of the first step of a particle physics analysis: selection, filtering, basic vector operations, and…
Context: The efficient processing of Big Data is a challenging task for SQL and NoSQL Databases, where competent software architecture plays a vital role. The SQL Databases are designed for structuring data and supporting vertical…
Multidimensional databases support efficiently on-line analytical processing (OLAP). In this paper, we depict a model dedicated to multidimensional databases. The approach we present designs decisional information through a constellation of…
This paper addresses emerging system-level challenges in heterogeneous retrieval-augmented generation (RAG) serving, where complex multi-stage workflows and diverse request patterns complicate efficient execution. We present HedraRAG, a…
Bitmap indexes are widely used for read-intensive analytical workloads because they are clustered and offer efficient reads with a small memory footprint. However, they are notoriously inefficient to update. As analytical applications are…
Large language models produce powerful text embeddings, but their causal attention mechanism restricts the flow of information from later to earlier tokens, degrading representation quality. While recent methods attempt to solve this by…
Graph databases (GDB) have recently been arisen to overcome the limits of traditional databases for storing and managing data with graph-like structure. Today, they represent a requirement for many applications that manage graph-like data,…
In recent years, the increased need to house and process large volumes of data has prompted the need for distributed storage and querying systems. The growth of machine-readable RDF triples has prompted both industry and academia to develop…
Concurrency Control (CC) ensuring consistency of updated data is an essential element of OLTP systems. Recently, hybrid transactional/analytical processing (HTAP) systems developed for executing OLTP and OLAP have attracted much attention.…
Tabular data, widely used in industries like healthcare, finance, and transportation, presents unique challenges for deep learning due to its heterogeneous nature and lack of spatial structure. This survey reviews the evolution of deep…
This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach. Unlike existing tools, our…
Over the past decade, the data lake concept has emerged as an alternative to data warehouses for storing and analyzing big data. A data lake allows storing data without any predefined schema. Therefore, data querying and analysis depend on…
Foundation models have impressive performance and generalization capabilities across a wide range of applications. The increasing size of the models introduces great challenges for the training. Tensor parallelism is a critical technique…
This paper deals with memory management issues of robotics. In our proposal we break one of the major issues in creating humanoid. . Database issue is the complicated thing in robotics schema design here in our proposal we suggest new…
TalkBank is an online database that facilitates the sharing of linguistics research data. However, the existing TalkBank's API has limited data filtering and batch processing capabilities. To overcome these limitations, this paper…
Modern data analytics pipelines increasingly combine relational queries, graph processing, and tensor computation within a single application, but existing systems remain fragmented across paradigms, execution models, and research…