MulTe: A Multi-Tenancy Database Benchmark Framework

Multi-tenancy in relational databases has been a topic of interest for a couple of years. On the one hand, ever increasing capabilities and capacities of modern hardware easily allow for multiple database applications to share one system. On the other hand, cloud computing leads to outsourcing of many applications to service architectures, which in turn leads to offerings for relational databases in the cloud, as well. The ability to benchmark multi-tenancy database systems (MT-DBMSs) is imperative to evaluate and compare systems and helps to reveal otherwise unnoticed shortcomings. With several tenants sharing a MT-DBMS, a benchmark is considerably different compared to classic database benchmarks and calls for new benchmarking methods and performance metrics. Unfortunately, there is no single, well-accepted multi-tenancy benchmark for MT-DBMSs available and few efforts have been made regarding the methodology and general tooling of the process. We propose a method to benchmark MT-DBMSs and provide a framework for building such benchmarks. To support the cumbersome process of defining and generating tenants, loading and querying their data, and analyzing the results we propose and provide MULTE, an open-source framework that helps with all these steps

DBaaS Multitenancy, Auto-tuning and SLA Maintenance in Cloud Environments: a Brief Survey

Cloud computing is a paradigm that presents many advantages to both costumers and service providers, such as low upfront investment, pay-per-use and easiness of use, delivering/enabling scalable services using Internet technologies. Among many types of services we have today, Database as a Service (DBaaS) is the one where a database is provided in the cloud in all its aspects. Examples of aspects related to DBaaS utilization are data storage, resources management and SLA maintenance. In this context, an important feature, related to it, is resource management and performance, which can be done in many different ways for several reasons, such as saving money, time, and meeting the requirements agreed between client and provider, that are defined in the Service Level Agreement (SLA). A SLA usually tries to protect the costumer from not receiving the contracted service and to ensure that the provider reaches the profit intended. In this paper it is presented a classification based on three main parameters that aim to manage resources for enhancing the performance on DBaaS and guarantee that the SLA is respected for both user and provider sides benefit. The proposal is based upon a survey of existing research work efforts

A Review Of Multi-Tenant Database And Factors That Influence Its Adoption.

A Multi-tenant database (MTD) is a way of deploying a Database as a Service (DaaS). This is gaining momentum with significant increase in the number of organizations ready to take advantage of the technology. A multi-tenant database refers to a principle where a single instance of a Database Management System (DBMS) runs on a server, serving multiple clients organizations (tenants). This is a database which provides database support to a number of separate and distinct groups of users or tenants. This concept spreads the cost of hardware, software and other services to a large number of tenants, therefore significantly reducing per tenant cost. Three different approaches of implementing multi-tenant database have been identified. These methods have been shown to be increasingly better at pooling resources and also processing administrative operations in bulk. This paper reports the requirement of multi-tenant databases, challenges of implementing MTD, database migration for elasticity in MTD and factors influencing the choice of models in MTD. An insightful discussion is presented in this paper by grouping these factors into four categories. This shows that the degree of tenancy is an influence to the approach to be adopted and the capital and operational expenditure are greatly reduced in comparison with an on-premises solutio

A Query, a Minute: Evaluating Performance Isolation in Cloud Databases

Several cloud providers offer reltional databases as part of their portfolio. It is however not obvious how resource virtualization and sharing, which is inherent to cloud computing, influence performance and predictability of these cloud databases. Cloud providers give little to no guarantees for consistent execution or isolation from other users. To evaluate the performance isolation capabilities of two commercial cloud databases, we ran a series of experiments over the course of a week (a query, a minute) and report variations in query response times. As a baseline, we ran the same experiments on a dedicated server in our data center. The results show that in the cloud single outliers are up to 31 times slower than the average. Additionally, one can see a point in time after which the average performance of all executed queries improves by 38 %

MapperMania: A Framework for Native Multi-Tenancy Business Object Mapping to a Persistent Data Source

The Software-as-a-Service delivery model bears new challenges for application developers. Especially in the context of enterprise resource planning software targeting the SME market, new problems arise. Most of them agglomerate around the occurrence of multi-tenancy. This paper describes the framework MapperMania which aims to establish an abstraction layer between the persistence layer and the domain model. Leveraging MapperMania, the domain model is able to abstract from multi-tenancy and changes in the underlying infrastructure

Invisible Deployment of Integration Processes

Due to the changing scope of data management towards the management of heterogeneous and distributed systems and applications, integration processes gain in importance. This is particularly true for those processes used as abstractions of workflow-based integration tasks; these are widely applied in practice. In such scenarios, a typical IT infrastructure comprises multiple integration systems with overlapping functionalities. The major problems in this area are high development effort, low portability and inefficiency. Therefore, in this paper, we introduce the vision of invisible deployment that addresses the virtualization of multiple, heterogeneous, physical integration systems into a single logical integration system. This vision comprises several challenging issues in the fields of deployment aspects as well as runtime aspects. Here, we describe those challenges, discuss possible solutions and present a detailed system architecture for that approach. As a result, the development effort can be reduced and the portability as well as the performance can be improved significantly

Designee of a Scalable Database Management Systems (DBMS)

Scalable database management systems (DBMS)-both for update intensive application workloads as well as decision support systems for descriptive and deep analytics-are a critical part of the cloud infrastructure and play an important role in ensuring the smooth transition of applications from the traditional enterprise infrastructures to next generation cloud infrastructures. Though scalable data management has been a vision for more than three decades and much research has focused on large scale data management in traditional enterprise setting, cloud computing brings its own set of novel challenges that must be addressed to ensure the success of data management solutions in the cloud environment. This tutorial presents an organized picture of the challenges faced by application developers and DBMS designers in developing and deploying internet scale applications. Our background study encompasses both classes of systems: (I) for supporting update heavy applications and (II) for ad-hoc analytics and decision support. We then focus on providing an in-depth analysis of systems for supporting update intensive web-applications and provide a survey of the state-of-the-art in this domain. We crystallize the design choices made by some successful systems large scale database management systems, analyze the application demands and access patterns, and enumerate the desiderata for a cloud-bound DBMS

Проектирование и разработка имитационной модели мультиклиентского кластера баз данных

One of the main trends of recent years in software design is a shift to a Software as a Service (SaaS) paradigm which brings a number of advantages for both software developers and end users. However, along with these benefits this transition brings new architectural challenges. One of such challenges is the implementation of a data storage that would meet the needs of a service-provider, at the same time providing a fairly simple application programming interface for software developers. In order to develop effective solutions in this area, the architectural features of cloud-based applications should be taken into account. Among others, such key features are the need for scalability and quick adaptation to changing conditions. This paper provides a brief analysis of the problems in the field of cloud data storage systems based on the relational model and it proposes the concept of database cluster designed for applications with a multi-tenant architecture. Besides, the article describes a simulation model of such a cluster, as well as the main stages of its development and the main principles forming its foundation.Одной из главных тенденций последних лет в проектировании программного обеспечения стал переход к парадигме Software as a Service (SaaS), которая несет ряд неоспоримых преимуществ как для компаний-разработчиков ПО, так и для конечных пользователей. Однако вместе с этими преимуществами данный переход несет и новые архитектурные вызовы, одним из которых является организация хранилища данных, которое могло бы удовлетворить нужды компании-провайдера услуг, обеспечив достаточно простой прикладной интерфейс для разработчиков. Для разработки эффективного решения в данной области следует принимать во внимание особенности архитектуры облачных приложений, ключевыми из которых являются потребность в простом масштабировании и быстрой адаптации к меняющимся условиям. В данной работе проводится краткий анализ существующих проблем в области организации облачных систем хранения данных, основанных на реляционной модели, а также предлагается концепция кластера РСУБД, предназначенного для обслуживания приложений с мультиклиентской архитектурой. Кроме того, в статье дается описание имитационной модели подобного кластера, а также основных этапов ее разработки и принципов, заложенных в ее основу

Statistical analysis of factors that influences the evaluation and adoption of multi-tenant databases

Multi-tenant Databases (MTD) are implemented in the deployment of database management services to Information Technology (IT) platform users. A database service provider hosts the Multi-tenant Database Management System (MTDMS) and each tenant subscribes to the service through a standard method such as a web service. Improved groupings of the factors that influence the adoption of MTDs are presented in this paper. A survey is presented here that involves forty one experts from the field of databases. A predictive analytical method called Relative Importance Index (RII) and other statistical tools have been adopted in the analysis. The result has led to the new framework in the adoption of MTDs. The research also considers the direction of decisions about MTDs in situations where two or more factors are combined. A new improved MTD framework is presented that improves the decision making process of MTD adoption.Published onlin