Nosql – Factors Supporting the Adoption of Non-Relational Databases
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Socrates: the New SQL Server in the Cloud
Socrates: The New SQL Server in the Cloud Panagiotis Antonopoulos, Alex Budovski, Cristian Diaconu, Alejandro Hernandez Saenz, Jack Hu, Hanuma Kodavalla, Donald Kossmann, Sandeep Lingam, Umar Farooq Minhas, Naveen Prakash, Vijendra Purohit, Hugh Qu, Chaitanya Sreenivas Ravella, Krystyna Reisteter, Sheetal Shrotri, Dixin Tang, Vikram Wakade Microsoft Azure & Microsoft Research ABSTRACT 1 INTRODUCTION The database-as-a-service paradigm in the cloud (DBaaS) The cloud is here to stay. Most start-ups are cloud-native. is becoming increasingly popular. Organizations adopt this Furthermore, many large enterprises are moving their data paradigm because they expect higher security, higher avail- and workloads into the cloud. The main reasons to move ability, and lower and more flexible cost with high perfor- into the cloud are security, time-to-market, and a more flexi- mance. It has become clear, however, that these expectations ble “pay-as-you-go” cost model which avoids overpaying for cannot be met in the cloud with the traditional, monolithic under-utilized machines. While all these reasons are com- database architecture. This paper presents a novel DBaaS pelling, the expectation is that a database runs in the cloud architecture, called Socrates. Socrates has been implemented at least as well as (if not better) than on premise. Specifically, in Microsoft SQL Server and is available in Azure as SQL DB customers expect a “database-as-a-service” to be highly avail- Hyperscale. This paper describes the key ideas and features able (e.g., 99.999% availability), support large databases (e.g., of Socrates, and it compares the performance of Socrates a 100TB OLTP database), and be highly performant. -
CA SQL-Ease for DB2 for Z/OS User Guide
CA SQL-Ease® for DB2 for z/OS User Guide Version 17.0.00, Second Edition This Documentation, which includes embedded help systems and electronically distributed materials, (hereinafter referred to as the “Documentation”) is for your informational purposes only and is subject to change or withdrawal by CA at any time. This Documentation is proprietary information of CA and may not be copied, transferred, reproduced, disclosed, modified or duplicated, in whole or in part, without the prior written consent of CA. If you are a licensed user of the software product(s) addressed in the Documentation, you may print or otherwise make available a reasonable number of copies of the Documentation for internal use by you and your employees in connection with that software, provided that all CA copyright notices and legends are affixed to each reproduced copy. The right to print or otherwise make available copies of the Documentation is limited to the period during which the applicable license for such software remains in full force and effect. Should the license terminate for any reason, it is your responsibility to certify in writing to CA that all copies and partial copies of the Documentation have been returned to CA or destroyed. TO THE EXTENT PERMITTED BY APPLICABLE LAW, CA PROVIDES THIS DOCUMENTATION “AS IS” WITHOUT WARRANTY OF ANY KIND, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NONINFRINGEMENT. IN NO EVENT WILL CA BE LIABLE TO YOU OR ANY THIRD PARTY FOR ANY LOSS OR DAMAGE, DIRECT OR INDIRECT, FROM THE USE OF THIS DOCUMENTATION, INCLUDING WITHOUT LIMITATION, LOST PROFITS, LOST INVESTMENT, BUSINESS INTERRUPTION, GOODWILL, OR LOST DATA, EVEN IF CA IS EXPRESSLY ADVISED IN ADVANCE OF THE POSSIBILITY OF SUCH LOSS OR DAMAGE. -
Server New Features Webfocus Server Release 8207 Datamigrator Server Release 8207
Server New Features WebFOCUS Server Release 8207 DataMigrator Server Release 8207 February 26, 2021 Active Technologies, FOCUS, Hyperstage, Information Builders, the Information Builders logo, iWay, iWay Software, Omni- Gen, Omni-HealthData, Parlay, RStat, Table Talk, WebFOCUS, WebFOCUS Active Technologies, and WebFOCUS Magnify are registered trademarks, and DataMigrator, and ibi are trademarks of Information Builders, Inc. Adobe, the Adobe logo, Acrobat, Adobe Reader, Flash, Adobe Flash Builder, Flex, and PostScript are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States and/or other countries. Due to the nature of this material, this document refers to numerous hardware and software products by their trademarks. In most, if not all cases, these designations are claimed as trademarks or registered trademarks by their respective companies. It is not this publisher's intent to use any of these names generically. The reader is therefore cautioned to investigate all claimed trademark rights before using any of these names other than to refer to the product described. Copyright © 2021. TIBCO Software Inc. All Rights Reserved. Contents 1. Server Enhancements ........................................................ 11 Global WebFOCUS Server Monitoring Console ........................................... 11 Server Text Editor Supports Jump to Next or Previous Difference in Compare and Merge .......14 Upload Message Added in the Edaprint Log ............................................. 15 Displaying the -
Oracle, IBM DB2, and SQL RDBMS’
Enterprise Architecture Technical Brief Oracle, IBM DB2, and SQL RDBMS’ Robert Kowalke November 2017 Enterprise Architecture Oracle, IBM DB2, and SQL RDBMS Contents Database Recommendation ............................................................................................................. 3 Relational Database Management Systems (RDBMS) ................................................................... 5 Oracle v12c-r2 ............................................................................................................................ 5 IBM DB2 for Linux, Unix, Windows (LUW) ............................................................................ 6 Microsoft SQL Server (Database Engine) v2017 ...................................................................... 7 Additional Background Information ............................................................................................... 9 VITA Reference Information (To be removed) ......................... Error! Bookmark not defined. Page 2 of 15 [email protected] Enterprise Architecture Oracle, IBM DB2, and SQL RDBMS Database Recommendation Oracle, SQL Server, and DB2 are powerful RDBMS options. There are a number of differences in how they work “under the hood,” and in various situations, one may be more favorable than the other. 1 There is no easy answer, nor is there a silver-bullet for choosing one of these three (3) databases for your specific business requirements. Oracle is a very popular choice with the Fortune 100 list of companies and -
Adapting a Synonym Database to Specific Domains Davide Turcato Fred Popowich Janine Toole Dan Pass Devlan Nicholson Gordon Tisher Gavagai Technology Inc
Adapting a synonym database to specific domains Davide Turcato Fred Popowich Janine Toole Dan Pass Devlan Nicholson Gordon Tisher gavagai Technology Inc. P.O. 374, 3495 Ca~abie Street, Vancouver, British Columbia, V5Z 4R3, Canada and Natural Language Laboratory, School of Computing Science, Simon Fraser University 8888 University Drive, Burnaby, British Columbia, V5A 1S6, Canada {turk, popowich ,toole, lass, devl an, gt i sher}@{gavagai, net, as, sfu. ca} Abstract valid for English, would be detrimental in a specific domain like weather reports, where This paper describes a method for both snow and C (for Celsius) occur very fre- adapting a general purpose synonym quently, but never as synonyms of each other. database, like WordNet, to a spe- We describe a method for creating a do- cific domain, where only a sub- main specific synonym database from a gen- set of the synonymy relations de- eral purpose one. We use WordNet (Fell- fined in the general database hold. baum, 1998) as our initial database, and we The method adopts an eliminative draw evidence from a domain specific corpus approach, based on incrementally about what synonymy relations hold in the pruning the original database. The domain. method is based on a preliminary Our task has obvious relations to word manual pruning phase and an algo- sense disambiguation (Sanderson, 1997) (Lea- rithm for automatically pruning the cock et al., 1998), since both tasks are based database. This method has been im- on identifying senses of ambiguous words in plemented and used for an Informa- a text. However, the two tasks are quite dis- tion Retrieval system in the aviation tinct. -
An Approach to Deriving Global Authorizations in Federated Database Systems
5 An Approach To Deriving Global Authorizations in Federated Database Systems Silvana Castano Universita di Milano Dipartimento di Scienze dell'lnformazione, Universita di Milano Via Comelico 99/41, Milano, Italy. Email: castano @ds i. unimi. it Abstract Global authorizations in federated database systems can be derived from local authorizations exported by component databases. This paper addresses problems related to the development of techniques for the analysis of local authorizations and for the construction of global authorizations where semantic correspondences between subjects in different component databases are identified on the basis of authorization compatibility. Abstraction of compatible authorizations is discussed to semi-automatically derive global authorizations that are consistent with the local ones. Keywords Federated database systems, Discretionary access control, Authorization compati bility, Authorization abstraction. 1 INTRODUCTION A federated database system (or federation) is characterized by a number of com ponent databases (CDB) which share part of their data, while preserving their local autonomy. In particular, in the so-called tightly coupled systems [She90], a feder ation administrator (FDBA) is responsible for managing the federation and for defining a federated schema. A federated schema is an integrated description of all data exported by CDBs of the federation, obtained by resolving possible semantic conflicts among data descriptions [Bri94,Ham93,Sie91]. A basic security requirement of federated systems is that the autonomy of CDBs must be taken into account for access control [Mor92]. This means that global accesses to objects of a federated schema must be authorized also by the involved CDBs, according to their local security policies. Two levels of authorization can be distinguished: a global level, where global requests of federated users are evaluated P. -
Incorporating Trustiness and Collective Synonym/Contrastive Evidence Into Taxonomy Construction
Incorporating Trustiness and Collective Synonym/Contrastive Evidence into Taxonomy Construction #1 #2 3 Luu Anh Tuan , Jung-jae Kim , Ng See Kiong ∗ #School of Computer Engineering, Nanyang Technological University, Singapore [email protected], [email protected] ∗Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore [email protected] Abstract Previous works on the task of taxonomy con- struction capture information about potential tax- Taxonomy plays an important role in many onomic relations between concepts, rank the can- applications by organizing domain knowl- didate relations based on the captured information, edge into a hierarchy of is-a relations be- and integrate the highly ranked relations into a tax- tween terms. Previous works on the taxo- onomic structure. They utilize such information nomic relation identification from text cor- as hypernym patterns (e.g. A is a B, A such as pora lack in two aspects: 1) They do not B) (Kozareva et al., 2008), syntactic dependency consider the trustiness of individual source (Drumond and Girardi, 2010), definition sentences texts, which is important to filter out in- (Navigli et al., 2011), co-occurrence (Zhu et al., correct relations from unreliable sources. 2013), syntactic contextual similarity (Tuan et al., 2) They also do not consider collective 2014), and sibling relations (Bansal et al., 2014). evidence from synonyms and contrastive terms, where synonyms may provide ad- They, however, lack in the three following as- ditional supports to taxonomic relations, pects: 1) Trustiness: Not all sources are trust- while contrastive terms may contradict worthy (e.g. gossip, forum posts written by them. -
Oracle Nosql Database and DMS for Enhancing Iot Environments
How Oracle NoSQL Database and Oracle Database Mobile Server Enhance an Internet of Things Data Management Solution ORACLE WHITE P A P E R | JANUARY 2017 Table of Contents Introduction 1 IoT Explained and Data Volumes 1 Business Value 1 Critical Components of an High Performance IoT Environment 2 Basic Architecture 2 Edge Filtering 2 Oracle NoSQL Database Benefits 3 Oracle NoSQL Database Architecture 3 Edge Filtering and the Database Mobile Server 4 Oracle Database Mobile Server Benefits 4 Lambda Architecture 5 Existing Oracle IoT Cloud Service 6 Oracle Technologies 6 Summary 7 HOW ORACLE NOSQL DATABASE AND ORACLE DATABASE MOBILE SERVER ENHANCE AN INTERNET OF THINGS DATA MANAGEMENT SOLUTION Introduction The Internet of Things (IoT) has become an important technology that can facilitate both personal and organizational understanding of the devices that matter. As smart devices become more ubiquitous, architectures need to be put in place that effectively and efficiently deal with the wide range of devices and environments that will exist. This includes scenarios where data is streaming over a network as well as periods where data is produced but the devices are off-line. An IoT strategy can open up new businesses and increase the understanding of existing, intelligent products and services. The business benefits of understanding the massive amounts of data flowing into analytics systems will be impressive. IoT is bridging the gap between IT (Information Technology) and OT (operations technology) to derive insights towards controlling the costs for various industries such as manufacturing, retail, logistics etc. For all those organizations that are implementing IoT strategies, data management will be at the centre of this digital transformation and a key differentiator would be the ability to derive meaningful business insights from gathered data against organizations that will merely gather data. -
A Dictionary of DBMS Terms
A Dictionary of DBMS Terms Access Plan Access plans are generated by the optimization component to implement queries submitted by users. ACID Properties ACID properties are transaction properties supported by DBMSs. ACID is an acronym for atomic, consistent, isolated, and durable. Address A location in memory where data are stored and can be retrieved. Aggregation Aggregation is the process of compiling information on an object, thereby abstracting a higher-level object. Aggregate Function A function that produces a single result based on the contents of an entire set of table rows. Alias Alias refers to the process of renaming a record. It is alternative name used for an attribute. 700 A Dictionary of DBMS Terms Anomaly The inconsistency that may result when a user attempts to update a table that contains redundant data. ANSI American National Standards Institute, one of the groups responsible for SQL standards. Application Program Interface (API) A set of functions in a particular programming language is used by a client that interfaces to a software system. ARIES ARIES is a recovery algorithm used by the recovery manager which is invoked after a crash. Armstrong’s Axioms Set of inference rules based on set of axioms that permit the algebraic mani- pulation of dependencies. Armstrong’s axioms enable the discovery of minimal cover of a set of functional dependencies. Associative Entity Type A weak entity type that depends on two or more entity types for its primary key. Attribute The differing data items within a relation. An attribute is a named column of a relation. Authorization The operation that verifies the permissions and access rights granted to a user. -
Linear Scalability of Distributed Applications
Linear Scalability of Distributed Applications THÈSE NO 5278 (2012) PRÉSENTÉE LE 3 FÉVRIER 2012 À LA FACULTÉ INFORMATIQUE ET COMMUNICATIONS LABORATOIRE DE SYSTÈMES D'INFORMATION RÉPARTIS PROGRAMME DOCTORAL EN INFORMATIQUE, COMMUNICATIONS ET INFORMATION ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES PAR Nicolas Bonvin acceptée sur proposition du jury: Prof. B. Faltings, président du jury Prof. K. Aberer, directeur de thèse Prof. A. Ailamaki, rapporteur Prof. D. Kossmann, rapporteur Prof. C. Pu, rapporteur Suisse 2012 R´esum´e L’explosion des applications sociales, du commerce electronique´ ou de la recherche sur Internet a cre´e´ le besoin de nouvelles technologies et de systemes` adaptes´ au traitement et a` la gestion efficace d’un nombre considerable´ de donnees´ et d’utilisateurs. Ces applications doivent fonc- tionner sans interruption tous les jours de l’annee,´ et doivent donc etreˆ capables de survivre a` de subites et brutales montees´ en charge, ainsi qu’a` toutes sortes de defaillances´ logicielles, materielles,´ humaines et or- ganisationnelles. L’augmentation (ou la diminution) elastique´ et extensible des ressources affectees´ a` une application distribuee,´ tout en satisfaisant des exigences de disponibilite´ et de performance, est essentielle pour la viabilite´ com- merciale mais presente´ de grands defis´ pour les infrastructures actuelles. En effet, le Cloud Computing permet de fournir des ressources a` la de- mande: il devient desormais´ aise´ de demarrer´ des dizaines de serveurs en parallele` (ressources de calcul) ou de stocker un tres` grand nombre de donnees´ (ressources de stockage), memeˆ pour une duree´ tres` limitee,´ en payant uniquement pour les ressources consommees.´ Toutefois, ces infrastructures complexes constituees´ de ressources het´ erog´ enes` a` faible coutˆ sont sujettes aux pannes. -
DB2 Federated Systems Guide Step 6: Create the Nicknames for Tables Chapter 11
® ™ IBM DB2 Universal Database Federated Systems Guide Ve r s i o n 8 GC27-1224-00 ® ™ IBM DB2 Universal Database Federated Systems Guide Ve r s i o n 8 GC27-1224-00 Before using this information and the product it supports, be sure to read the general information under Notices. This document contains proprietary information of IBM. It is provided under a license agreement and is protected by copyright law. The information contained in this publication does not include any product warranties, and any statements provided in this manual should not be interpreted as such. You can order IBM publications online or through your local IBM representative. v To order publications online, go to the IBM Publications Center at www.ibm.com/shop/publications/order v To find your local IBM representative, go to the IBM Directory of Worldwide Contacts at www.ibm.com/planetwide To order DB2 publications from DB2 Marketing and Sales in the United States or Canada, call 1-800-IBM-4YOU (426-4968). When you send information to IBM, you grant IBM a nonexclusive right to use or distribute the information in any way it believes appropriate without incurring any obligation to you. © Copyright International Business Machines Corporation 1998 - 2002. All rights reserved. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Figures .............ix Application programs ........30 Tables ..............xi Chapter 2. Business Solutions with federated systems .........31 About this book ..........xiii Leverage the federated functionality to solve Who should read this book.......xiv your business needs .........31 Conventions and terminology used in this Replication with a federated system ....31 book ..............xiv Spatial analysis with a federated system . -
Comparison of Nosql and SQL Databases in the Cloud
Hammes, Medero, et al. NoSQL and SQL Databases Comparison of NoSQL and SQL Databases in the Cloud Dayne Hammes Hiram Medero Georgia Southern University Georgia Southern University [email protected] [email protected] Harrison Mitchell Georgia Southern University [email protected] ABSTRACT In this paper, we examine the design, execution, and subsequent performance between traditional Relational Database Management Systems (RDBMS) and modern NoSQL Database Systems, when implemented on a cloud server. While significant groundwork has been laid for this comparison, we will present two distinct scenarios for real-world comparison: one containing highly structured data, and one containing unstructured data. In addition to concerns of design, we will test our approaches to each model side-by-side in the same cloud environment. Keywords NoSQL, RDBMS, SQL, Cloud, Big Data, MongoDB, PostgreSQL, Elasticity, Structured Data, Unstructured Data INTRODUCTION The rise of cloud computing in the business consciousness has opened an ongoing debate regarding the pros and cons of using traditional Relational Database Management Systems or document and key-value based NoSQL (Not- Only SQL) implementations. Cloud computing was first utilized in the 1950’s, but only after the dot-com bubble burst of the early 2000’s did it grow into the standard we know today. Amazon’s Elastic Compute Cloud (EC2) on the AWS platform was released in 2006 and took advantage of low-cost servers and high-bandwidth networks first offered by Grid and Utility computing methods.[1] The merits of reliability, scalability and accessibility of data quickly led the public to see the values of using Infrastructure-as-a-Service over dedicated or shared hosting solutions, and several copycat companies have sprung up in recent years as a result.