Related papers: Odysseus/DFS: Integration of DBMS and Distributed …
One of the key advances in resolving the big-data problem has been the emergence of an alternative database technology. Today, classic RDBMS are complemented by a rich set of alternative Data Management Systems (DMS) specially designed to…
The metadata service (MDS) sits on the critical path for distributed file system (DFS) operations, and therefore it is key to the overall performance of a large-scale DFS. Common "serverful" MDS architectures, such as a single server or…
Database Management Systems (DBMSs) are widely used to store, retrieve, and manage the data handled by modern applications. Although prior work has studied the co-evolution of DBMSs and application source code, less is known about DBMS…
The rate at which data is generated has been increasing rapidly, raising challenges related to its management. Traditional database management systems suffer from scalability and are usually inefficient when dealing with large-scale and…
Current operating systems are complex systems that were designed before today's computing environments. This makes it difficult for them to meet the scalability, heterogeneity, availability, and security challenges in current cloud and…
This extended report presents DDS, a novel disaggregated storage architecture enabled by emerging networking hardware, namely DPUs (Data Processing Units). DPUs can optimize the latency and CPU consumption of disaggregated storage servers.…
HRDBMS is a novel distributed relational database that uses a hybrid model combining the best of traditional distributed relational databases and Big Data analytics platforms such as Hive. This allows HRDBMS to leverage years worth of…
Digital world is growing very fast and become more complex in the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), velocity (high speed in growth) in nature. This refers to as Big Data that is a global…
Distributed File Systems (DFS) have emerged as sophisticated solutions for efficient file storage and management across interconnected computer nodes. The main objective of DFS is to achieve flexible, scalable, and resilient file storage…
Recent improvements in both the performance and scalability of shared-nothing, transactional, in-memory NewSQL databases have reopened the research question of whether distributed metadata for hierarchical file systems can be managed using…
Disaggregated storage systems improve resource utilization and enable independent scaling of storage and compute resources by separating storage resources from computing resources in data centers. NVMe over fabrics (NVMeoF) is a key…
Distributed File Systems (DFS) are essential for managing vast datasets across multiple servers, offering benefits in scalability, fault tolerance, and data accessibility. This paper presents a comprehensive evaluation of three prominent…
This paper presents an architecture, based on Distributed Ledger Technologies (DLTs) and Decentralized File Storage (DFS) systems, to support the use of Personal Information Management Systems (PIMS). DLT and DFS are used to manage data…
Recently, parallel search engines have been implemented based on scalable distributed file systems such as Google File System. However, we claim that building a massively-parallel search engine using a parallel DBMS can be an attractive…
AsterixDB is a new, full-function BDMS (Big Data Management System) with a feature set that distinguishes it from other platforms in today's open source Big Data ecosystem. Its features make it well-suited to applications like web data…
Multi-tenancy hosting of users in cloud NoSQL data stores is favored by cloud providers because it enables resource sharing at low operating cost. Multi-tenancy takes several forms depending on whether the back-end file system is a local…
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…
A new emerging class of parallel database management systems (DBMS) is designed to take advantage of the partitionable workloads of on-line transaction processing (OLTP) applications. Transactions in these systems are optimized to execute…
Modern applications demand high performance and cost efficient database management systems (DBMSs). Their workloads may be diverse, ranging from online transaction processing to analytics and decision support. The cloud infrastructure…
In the current context of Big Data, a multitude of new NoSQL solutions for storing, managing, and extracting information and patterns from semi-structured data have been proposed and implemented. These solutions were developed to relieve…