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About 6,186 papers for “database scalability”

Database Scalability

Peter Lake, Paul Crowther · Undergraduate topics in computer science · 2013

Cited by 0

Array Database Scalability

Alex Dumitru, Vlad Merticariu, Peter Baumann · 2016

With the deluge of scientific big data affecting a large variety of research institutions, support for large multidimensional arrays has gained traction in the database community in the past decade. Array databases aim to cover the gap left by traditional relational database systems in the domains of large scientific data by enabling researchers to efficiently store and process their data through rich declarative query languages. Such large amounts of data need effective systems that are able to distribute the processing at both local level, through exploitation of heterogeneous hardware as well as at network level, enabling both intra-cloud and intra-federation distribution of data and processing. In this demonstration we aim to showcase the capabilities of rasdaman by allowing users to execute queries that combine petabyte datasets stored at two institutions on different continents.

Cited by 8

Putting the “Scalability ” into Database Scalability Services

Charles Garrod, David Andersen, Anthony Tomasic · 2008

Applications deployed on the Internet are immediately accessible to a vast population of potential users, and as a result they tend to experience unpredictable and widely fluctuating demand. System administrators currently face a provisioning dilemma to address this demand: whether to (1) waste money by heavily overprovisioning systems, or (2) risk loss of availability during times of high demand. This problem is largely solved for static Web content, but existing approaches do not apply well to dynamic content produced by data-intensive Web applications for which a central database server limits scalability. To address this problem, we design and build a Database Scalability Service (DBSS), which can offer scalability to data-intensive Web applications as a third-party service much like Content Delivery Networks currently scale static Web content. The key challenge in building a DBSS is to enable the DBSS to off-load database requests from a content provider’s central database server while ensuring that the DBSS uses up-to-date, consistent data as the database is updated. In addition, a DBSS faces the additional problems of maintaining high quality of service for each content provider as well as guaranteeing the privacy of a content provider’s data. In this thesis, we focus on the scalability-related aspects of a DBSS. We design and evaluate a DBSS, called Ferdinand, that uses a multi-tiered caching architecture, with a local database cache at each Ferdinand

Cited by 0

Predicting replicated database scalability from standalone database profiling

Sameh Elnikety, Steven Dropsho, Emmanuel Cecchet et al. · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · 2009

This paper develops analytical models to predict through-put and response time of a replicated database using meas-urements of the workload on a standalone database. These models allow workload scalability to be estimated before the replicated system is deployed, making the technique useful for capacity planning and dynamic service provi-sioning. The models capture the scalability limits stemming from update propagation and aborts for both multi-master and single-master replicated databases that support snap-shot isolation.

Cited by 35Open access

Invalidation Clues for Database Scalability Services

Manjhi, Amit, Gibbons, Phillip B., Ailamaki, Anastassia et al. · Figshare · 2018

<em><em><em> </em></em></em><em><em><em>For their scalability needs, data-intensive Web applications can use a Database Scalability Service (DBSS), which caches applications’ query results and answers queries on their behalf. One way for applications to address their security/privacy concerns when using a DBSS is to encrypt all data that passes through the DBSS. Doing so, however, causes the DBSS to invalidate large regions of its cache when data updates occur. To invalidate more precisely, the DBSS needs help in order to know which results to invalidate; such help inevitably reveals some properties about the data. In this paper, we present </em></em></em><em><em><em> </em></em> </em>invalidation clues<em><em>, a general technique that enables applications to reveal little data to the DBSS, yet limit the number of unnecessary invalidations. Compared with previous approaches, invalidation clues provide applications significantly improved tradeoffs between security/privacy and scalability. Our experiments using three Web application benchmarks, on a prototype DBSS we have built, confirm that invalidation clues are indeed a low-overhead, effective, and general technique for applications to balance their privacy and scalability needs.</em></em>

Cited by 0Open access

Invalidation Clues for Database Scalability Services

Manjhi, Amit, Gibbons, Phillip B., Ailamaki, Anastasia et al. · KiltHub Repository · 2018

For their scalability needs, data-intensive Web applications can use a database scalability service (DBSS), which caches applications' query results and answers queries on their behalf. One way for applications to address their security/privacy concerns when using a DBSS is to encrypt all data that passes through the DBSS. Doing so, however, causes the DBSS to invalidate large regions of its cache when data updates occur. To invalidate more precisely, the DBSS needs help in order to know which results to invalidate; such help inevitably reveals some properties about the data. In this paper, we present invalidation clues, a general technique that enables applications to reveal little data to the DBSS, yet limit the number of unnecessary invalidations. Compared with previous approaches, invalidation clues provide applications significantly improved tradeoffs between security/privacy and scalability. Our experiments using three Web application benchmarks, on a prototype DBSS we have built, confirm that invalidation clues are indeed a low-overhead, effective, and general technique for applications to balance their privacy and scalability needs.

Cited by 0Open access

Object Database Scalability for Scientific Workloads

Julian Bunn Koen, Koen Holtman · 2007

this paper, we report on scalability tests of the Objectivity/DB object database [3] made on the 256-processor HP Exemplar located at Caltech&amp;apos;s Center for Advanced Computing Research. Our tests focused on the behaviour of the aggregate throughput as a function of the number of database clients, under various representative workloads, and using realistic (simulated) LHC event data

Cited by 0

Invalidation Clues for Database Scalability Services

Manjhi, Amit, Gibbons, Phillip B., Ailamaki, Anastassia et al. · KiltHub Repository · 2018

<em><em><em> </em></em></em><em><em><em>For their scalability needs, data-intensive Web applications can use a Database Scalability Service (DBSS), which caches applications’ query results and answers queries on their behalf. One way for applications to address their security/privacy concerns when using a DBSS is to encrypt all data that passes through the DBSS. Doing so, however, causes the DBSS to invalidate large regions of its cache when data updates occur. To invalidate more precisely, the DBSS needs help in order to know which results to invalidate; such help inevitably reveals some properties about the data. In this paper, we present </em></em></em><em><em><em> </em></em> </em>invalidation clues<em><em>, a general technique that enables applications to reveal little data to the DBSS, yet limit the number of unnecessary invalidations. Compared with previous approaches, invalidation clues provide applications significantly improved tradeoffs between security/privacy and scalability. Our experiments using three Web application benchmarks, on a prototype DBSS we have built, confirm that invalidation clues are indeed a low-overhead, effective, and general technique for applications to balance their privacy and scalability needs.</em></em>

Cited by 0Open access

Multi-Tenant Architecture: Enhancing Database Scalability with In-memory Database

Arpita Shah, Mrugendrasinh Rahevar, Ronak Patel et al. · 2025

In the era of Big Data and the Internet of Things (IoT), the need for scalable and efficient data storage and processing solutions has become more critical than ever. With the rapid growth of cloud-based applications, the volume of data being generated, transmitted, and analyzed has reached unprecedented levels, necessitating robust and adaptive computing infrastructures, necessitating the development of scalable database management systems that can handle the growing data needs. One promising approach to addressing this challenge is the use of a multi-tenant architecture, which allows multiple tenants (customers or organizations) to share the same database infrastructure while maintaining data isolation and security. This paper aims to explore the integration of in-memory databases with multi-tenancy. Specifically, this study aims to elucidate the motivations behind multi-tenant application requirements concerning the database engine and highlight essential design considerations for implementing tenancy in cloud-based in-memory databases.

Cited by 0

Database Optimization Strategies: Enhancing Performance and Scalability

N V Rama Sai Chalapathi Gupta Lakkimsetty · International Journal of Computer Science and Mobile Computing · 2023

Database optimization is critical for ensuring efficient data retrieval and storage, enabling high performance and scalability in modern applications. This paper explores comprehensive strategies for optimizing databases, focusing on query performance, schema design, caching, scalability, and cloud-based databases. Through an analysis of best practices and advanced techniques, this paper highlights methods to improve performance metrics and reduce bottlenecks, with a focus on practical implementation for real-world scenarios.

Cited by 1Open access

Cloud Database Scalability: Meeting Modern Enterprise Demands

Sai Venkata Kondapalli · World Journal of Advanced Engineering Technology and Sciences · 2025

Cloud database technologies have emerged as a critical solution for enterprises grappling with explosive data growth and unpredictable workload patterns. This comprehensive article examines how modern cloud database systems address enterprise scalability challenges through dynamic resource allocation, distributed architectures, and automated management capabilities. Further, we deep dive into the core scalability technologies, including horizontal and vertical scaling approaches, automatic scaling mechanisms, and distributed database architectures that enable organizations to handle exponentially growing datasets. The article further analyzes various database service models (DBaaS, cloud-native distributed databases, self-managed deployments), resource optimization strategies (connection pooling, query optimization, workload management), and crucial implementation considerations for successful cloud database migrations. Through real-world examples across industries, this article demonstrates how properly implementing these technologies allows enterprises to balance performance requirements with cost optimization while maintaining the business agility required in today's data-driven landscape.

Cited by 0Open access

Performance and Scalability of Client-Server Database Architectures

Alexios Delis, Nick Roussopoulos · 1992

Recent developments in software and hardware changed the way database systems are built and operate. In this paper we present database architectures based on the Client-Server paradigm and study their performance and scalability under different query/update workloads. The architectures are: Standard Client-Server, Client-Server with Multiple Disks, and Enhanced Client{Server. Data replication and client query result caching are used as the main mechanisms to improve the query throughput. The role of the server is to maintain system-wide data consistency and in the case of Enhanced Client-Server to selectively propagate updates on demand. Our study shows that except for the case of mostly update workloads, the Standard Client-Server architecture is outperformed by the other two architectures by one or more orders of magnitude. The Client-Server with Multiple Disks architecture offers performance comparable to that achieved by the Enhanced Client-Server for up to 100 clients, but the latter scales up a lot better for higher number of clients.

Cited by 52

Performance and Scalability of Client-Server Database Architectures

2008

Recent developments in software and hardware changed the way database systems are built and operate. In this paper we present database ar-chitectures based on the Client-Server paradigm and study their performance and scalability un-der different query/update workloads. The ar-chitectures are: Standard Client-Server, Client-Server with Multiple Disks, and Enhanced Client-Server. Data replication and client query result caching are used as the main mechanisms to improve the query throughput. The role of the server is to maintain system-wide data con-sistency and in the case of Enhanced Client-Server to selectively propagate updates on de-mand. Our study shows that except for the case of mostly update workloads, the Standard Client-Server architecture is outperformed by the other two architectures by one or more orders of magnitude. The Client-Server with Multiple Disks architecture offers performance compara-ble to that achieved by the Enhanced Client-Server for up to 100 clients, but the latter scales up a lot better for higher number of clients. 1

Cited by 0

Enhancing Parallelism and Scalability of Database-Centric Applications in Presence of Database Deadlocks

BM M. Hossain (7980509) · Figshare · 2014

Currently, in Database-Centric Applications (DCAs), database deadlocks are typically detected at runtime within database engines using special algorithms that analyze whether resources are held in cyclic \ndependencies, and these database engines resolve database deadlocks by \nforcibly breaking the hold-and-wait cycle. That is, once a deadlock \noccurs, the database rolls back one of the SQL statements that is \ninvolved in the circular wait. This resolution causes severe performance \ndegradation, since DCAs should repeat the rolled back SQL statements to \nensure functional correctness. Doing so not only reduces parallelism in \nexecuting SQL statements by databases, but also requires these databases to re-execute the same SQL statements thus decreasing the throughput and negatively affecting the scalability of the DCAs.\n\nWe present novel solutions to a fundamental problem of predicting and \npreventing database deadlocks (PD)2 in DCAs, and we rigorously evaluate \nthese solutions on several different open-source and commercial DCAs, \nsome of which still exhibit database deadlocks after having been used \nfor close to two decades. In evaluating (PD)2, we addressed various research questions that establish the effectiveness of our solutions.

Cited by 0Open access

Scalability, Availability, Reproducibility and Extensibility in Islamic Database Systems

Siddiqui, Umar, Youssef, Habiba, Sabour, Adel et al. · ArXiv.org · 2025

With the widespread of software systems and applications that serve the Islamic knowledge domain, several concerns arise. Authenticity and accuracy of the databases that back up these systems are questionable. With the excitement that some software developers and amateur researchers may have, false statements and incorrect claims may be made around numerical signs or miracles in the Quran. Reproducibility of these claims may not be addressed by the people making such claims. Moreover, with the increase in the number of users, scalability and availability of these systems become a concern. In addition to all these concerns, extensibility is also another major issue. Properly designed systems can be extensible, reusable and built on top of one another, instead of each system being built from scratch every time a new framework is developed. In this paper, we introduce the QuranResearch.Org system and its vision for scalability, availability, reproducibility and extensibility to serve Islamic database systems.

Cited by 0Open access