Oracle Database Mobile Server, Version 12.2
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Outline: Combining Brainstorming Deliverables Table of Contents 1. Introduction and Definition 2. Reference Architecture and Taxonomy 3. Requirements, Gap Analysis, and Suggested Best Practices 4. Future Directions and Roadmap 5. Security and Privacy - 10 Top Challenges 6. Conclusions and General Advice Appendix A. Terminology Glossary Appendix B. Solutions Glossary Appendix C. Use Case Examples Appendix D. Actors and Roles 1. Introduction and Definition The purpose of this outline is to illustrate how some initial brainstorming documents might be pulled together into an integrated deliverable. The outline will follow the diagram below. Section 1 introduces a definition of Big Data. An extended terminology Glossary is found in Appendix A. In section 2, a Reference Architecture diagram is presented followed by a taxonomy describing and extending the elements of the Reference Architecture. Section 3 maps requirements from use case building blocks to the Reference Architecture. A description of the requirement, a gap analysis, and suggested best practice is included with each mapping. In Section 4 future improvements in Big Data technology are mapped to the Reference Architecture. An initial Technology Roadmap is created on the requirements and gap analysis in Section 3 and the expected future improvements from Section 4. Section 5 is a placeholder for an extended discussion of Security and Privacy. Section 6 gives an example of some general advice. The Appendices provide Big Data terminology and solutions glossaries, Use Case Examples, and some possible Actors and Roles. Big Data Definition - “Big Data refers to the new technologies and applications introduced to handle increasing Volumes of data while enhancing data utilization capabilities such as Variety, Velocity, Variability, Veracity, and Value.” The key attribute is the large Volume of data available that forces horizontal scalability of storage and processing and has implications for all the other V-attributes. -
Use Case Guidance: Selecting the Best Apps for Mongodb, and When to Evaluate Other Options
Use Case Guidance: Selecting the best apps for MongoDB, and when to evaluate other options June 2020 Table of Contents Introduction 2 When Should I Use MongoDB? 2 MongoDB Database & Atlas: Transactional and Real-Time Analytics 3 MongoDB Atlas Data Lake: Long-Running Analytics 3 The MongoDB Data Platform 3 Key Strategic Initiatives Supported by MongoDB 4 Legacy Modernization 5 Cloud Data Strategy 5 Data as a Service (DaaS) 6 Business Agility 7 Use Cases for MongoDB 7 Single View 7 Customer Data Management and Personalization 9 Internet of Things (IoT) and Time-Series Data 10 Product Catalogs and Content Management 11 Payment Processing 13 Mobile Apps 14 Mainframe Offload 16 Operational Analytics and AI 17 Data Lake Analytics 20 Is MongoDB Always the Right Solution? 22 Common Off-the-Shelf Software Built for Relational Databases 22 CURRENT COPY: Ad-Hoc Reporting in the MongoDB Server: Unindexed Queries 22 PROPOSED REPLACEMENT COPY Assessing Analytics and Data Warehousing Use-Cases 22 Data Warehouse Replacements with Atlas Data Lake 24 Conclusion 25 We Can Help 26 Resources 27 1 Introduction Data and software are today at the heart of every business, but for many organizations, realizing the full potential of the digital economy remains a significant challenge. Since the inception of MongoDB, we’ve believed that as companies embrace digital transformation, their developers’ biggest challenges come from working with data: ● Demands for higher developer productivity and faster time to market – where release cycles are compressed to days and weeks – are being held back by rigid relational data models and traditional waterfall development practices. -
Mobile Application Architecture Guide
Mobile Application Architecture Guide Application Architecture Pocket Guide Series Mobile Application Pocket Guide v1.1 Information in this document, including URL and other Internet Web site references, is subject to change without notice. Unless otherwise noted, the example companies, organizations, products, domain names, e-mail addresses, logos, people, places, and events depicted herein are fictitious, and no association with any real company, organization, product, domain name, e-mail address, logo, person, place, or event is intended or should be inferred. Complying with all applicable copyright laws is the responsibility of the user. Without limiting the rights under copyright, no part of this document may be reproduced, stored in or introduced into a retrieval system, or transmitted in any form or by any means (electronic, mechanical, photocopying, recording, or otherwise), or for any purpose, without the express written permission of Microsoft Corporation. Microsoft may have patents, patent applications, trademarks, copyrights, or other intellectual property rights covering subject matter in this document. Except as expressly provided in any written license agreement from Microsoft, the furnishing of this document does not give you any license to these patents, trademarks, copyrights, or other intellectual property. 2008 Microsoft Corporation. All rights reserved. Microsoft, MS-DOS, Windows, Windows NT, Windows Server, Active Directory, MSDN, Visual Basic, Visual C++, Visual C#, Visual Studio, and Win32 are either registered trademarks or trademarks of Microsoft Corporation in the United States and/or other countries. The names of actual companies and products mentioned herein may be the trademarks of their respective owners. Microsoft patterns & practices 2 Mobile Application Pocket Guide v1.1 Mobile Application Architecture Guide patterns & practices J.D. -
Oracle Nosql Database
An Oracle White Paper November 2012 Oracle NoSQL Database Oracle NoSQL Database Table of Contents Introduction ........................................................................................ 2 Technical Overview ............................................................................ 4 Data Model ..................................................................................... 4 API ................................................................................................. 5 Create, Remove, Update, and Delete..................................................... 5 Iteration ................................................................................................... 6 Bulk Operation API ................................................................................. 7 Administration .................................................................................... 7 Architecture ........................................................................................ 8 Implementation ................................................................................... 9 Storage Nodes ............................................................................... 9 Client Driver ................................................................................. 10 Performance ..................................................................................... 11 Conclusion ....................................................................................... 12 1 Oracle NoSQL Database Introduction NoSQL databases -
Oracle Berkeley DB Installation and Build Guide Release 18.1
Oracle Berkeley DB Installation and Build Guide Release 18.1 Library Version 18.1.32 Legal Notice Copyright © 2002 - 2019 Oracle and/or its affiliates. All rights reserved. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. Berkeley DB, and Sleepycat are trademarks or registered trademarks of Oracle. All rights to these marks are reserved. No third- party use is permitted without the express prior written consent of Oracle. Other names may be trademarks of their respective owners. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, use, duplication, disclosure, modification, and adaptation of the programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, shall be subject to license terms and license restrictions applicable to the programs. -
Oracle® Nosql Database Changelog
Oracle® NoSQL Database Changelog Release 20.1 E91819-17 July 2020 Oracle NoSQL Database Changelog, Release 20.1 E91819-17 Copyright © 2011, 2020, Oracle and/or its affiliates. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs) and Oracle computer documentation or other Oracle data delivered to or accessed by U.S. Government end users are "commercial computer software" or “commercial computer software documentation” pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, reproduction, duplication, release, display, disclosure, modification, preparation of derivative works, and/or adaptation of i) Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs), ii) Oracle computer documentation and/or iii) other Oracle data, is subject to the rights and limitations specified in the license contained in the applicable contract. -
Oracle Database Vault Overview
Oracle Database Vault Oracle Database Vault provides controls to prevent unauthorized privileged users from accessing sensitive data, prevent unauthorized database changes, and helps customers meet industry, regulatory, or corporate security standards. March 23, 2020 Copyright © 2020, Oracle and/or its affiliates Public Purpose Statement This document provides an overview of features and enhancements included in the latest releases of Oracle Database Vault. It is intended solely to help you assess the business benefits of using Oracle Database Vault preventive controls and to plan your Data Security / I.T. projects. Disclaimer This document in any form, software or printed matter, contains proprietary information that is the exclusive property of Oracle. Your access to and use of this confidential material is subject to the terms and conditions of your Oracle software license and service agreement, which has been executed and with which you agree to comply. This document is not part of your license agreement nor can it be incorporated into any contractual agreement with Oracle or its subsidiaries or affiliates. This document is for informational purposes only and is intended solely to assist you in planning for the implementation and upgrade of the product features described. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described in this document remains at the sole discretion of -
Oracle Nosql Database and Cisco- Collaboration That Produces Results
Oracle NoSQL Database and Cisco- Collaboration that produces results 1 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. What is Big Data? SOCIAL BLOG SMART METER VOLUME VELOCITY VARIETY VALUE 2 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Why Is It Important? US HEALTH CARE US RETAIL MANUFACTURING GLOBAL PERSONAL EUROPE PUBLIC LOCATION DATA SECTOR ADMIN Increase industry Increase net Decrease dev., Increase service Increase industry value per year by margin by assembly costs by provider revenue by value per year by $300 B 60+% –50% $100 B €250 B “In a big data world, a competitor that fails to sufficiently develop its capabilities will be left behind.” 3 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Source: * McKinsey Global Institute: Big Data – The next frontier for innovation, competition and productivity (May 2011) Big Data in Action DECIDE ACQUIRE Make Better Decisions Using Big Data ANALYZE ORGANIZE 4 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Oracle Integrated Solution Stack DATA VARIETY HDFS HADOOP (MapReduce) In-DB Oracle Loader Mining for HADOOP Oracle NoSQL DB Oracle In-DB Exadata ‘R’ In-DB MapReduce OBIEE Oracle Data Analytics Advanced Oracle Database Integrator INFORMATION DENSITY ACQUIRE ORGANIZE ANALYZE DECIDE 5 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Big Data in Action DECIDE ACQUIRE Acquire all available, schema-based and non- relational data ANALYZE ORGANIZE 6 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. Acquiring Big Data Challenge Process high volume, low- Application changes With sub-millisecond density information frequently Velocity from various data-sets 7 Copyright © 2011, Oracle and/or its affiliates. -
Oracle Big Data SQL Release 4.1
ORACLE DATA SHEET Oracle Big Data SQL Release 4.1 The unprecedented explosion in data that can be made useful to enterprises – from the Internet of Things, to the social streams of global customer bases – has created a tremendous opportunity for businesses. However, with the enormous possibilities of Big Data, there can also be enormous complexity. Integrating Big Data systems to leverage these vast new data resources with existing information estates can be challenging. Valuable data may be stored in a system separate from where the majority of business-critical operations take place. Moreover, accessing this data may require significant investment in re-developing code for analysis and reporting - delaying access to data as well as reducing the ultimate value of the data to the business. Oracle Big Data SQL enables organizations to immediately analyze data across Apache Hadoop, Apache Kafka, NoSQL, object stores and Oracle Database leveraging their existing SQL skills, security policies and applications with extreme performance. From simplifying data science efforts to unlocking data lakes, Big Data SQL makes the benefits of Big Data available to the largest group of end users possible. KEY FEATURES Rich SQL Processing on All Data • Seamlessly query data across Oracle Oracle Big Data SQL is a data virtualization innovation from Oracle. It is a new Database, Hadoop, object stores, architecture and solution for SQL and other data APIs (such as REST and Node.js) on Kafka and NoSQL sources disparate data sets, seamlessly integrating data in Apache Hadoop, Apache Kafka, • Runs all Oracle SQL queries without modification – preserving application object stores and a number of NoSQL databases with data stored in Oracle Database. -
Oracle Database Advanced Application Developer's Guide, 11G Release 2 (11.2) E17125-03
Oracle® Database Advanced Application Developer's Guide 11g Release 2 (11.2) E17125-03 August 2010 Oracle Database Advanced Application Developer's Guide, 11g Release 2 (11.2) E17125-03 Copyright © 1996, 2010, Oracle and/or its affiliates. All rights reserved. Primary Author: Sheila Moore Contributing Authors: D. Adams, L. Ashdown, M. Cowan, J. Melnick, R. Moran, E. Paapanen, J. Russell, R. Strohm, R. Ward Contributors: D. Alpern, G. Arora, C. Barclay, D. Bronnikov, T. Chang, L. Chen, B. Cheng, M. Davidson, R. Day, R. Decker, G. Doherty, D. Elson, A. Ganesh, M. Hartstein, Y. Hu, J. Huang, C. Iyer, N. Jain, R. Jenkins Jr., S. Kotsovolos, V. Krishnaswamy, S. Kumar, C. Lei, B. Llewellyn, D. Lorentz, V. Moore, K. Muthukkaruppan, V. Moore, J. Muller, R. Murthy, R. Pang, B. Sinha, S. Vemuri, W. Wang, D. Wong, A. Yalamanchi, Q. Yu This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this software or related documentation is delivered to the U.S. -
Oracle Database Sharding Infographic
Oracle Database Sharding Oracle Sharding : Scale-out Rela7onal Database Sharding = Distributed Par77oning + Replica7on One giant database par66oned into many small databases (shards) Built on shared-nothing hardware architecture • Some web-scale OLTP applicaons use database sharding to avoid • Horizontal par66oning of data using a sharding key (e.g. scalability or availability edge cases of a single large database customer_id) across a farm of independent Oracle Databases • Oracle 12cR2 is the first full-featured RDBMS that provides nave • Shards can be hosted on commodity servers or engineered systems database sharding while suppor6ng enterprise capabili6es • Data automacally replicated with Data Guard or Oracle GoldenGate for high availability and disaster recovery Benefits Linear Scalability Fault Isola7on Geographic Distribuon Flexible Deployment 12,000,000 CPU CA On-Premises Hybrid Cloud 10,000,000 CA CA 8,000,000 … TPS 6,000,000 CA Vector Register 4,000,000 … 2,000,000 0 50 100 150 200 # of Shards Add shards online to Shared-nothing Data Sovereignty - for Flexible On-Premises, Cloud or Hybrid linearly scale - architecture. data privacy regulaons. Deployments. transac6ons, users and Fault of one shard Data Proximity - to bring Supports Cloud bursng database capacity has no impact on data closer to the users other shards Salient Features • Auto deployment of up to 1000 shards • Direct Rou6ng – Supports Data Guard and Oracle GoldenGate – Direct fast path SQL access via sharding key from smart topology- • Mul6ple sharding methods aware -
IBM Db2 Hosted Data Sheet
IBM Analytics Data sheet IBM Db2 Hosted The power of IBM Db2 software combined with the agility of cloud deployment — all under your control IBM Db2 Hosted: Your fast, economical choice Highlights The IBM Db2 solution is a multi-workload relational database system that can improve business agility and reduce costs by helping • Get the full-featured capabilities of you better manage your company’s core asset: data. And now, this IBM® Db2® Workgroup or IBM Db2 Advanced Enterprise Server system is available on demand as a cloud service, which provides the following advantages: • Support both transactional and analytics workloads • Rapid provisioning for nearly instant productivity • Migrate applications more easily thanks Avoid the usual lengthy wait for procurement and data center setup. to compatibility with IBM Db2 software and Oracle Database SQL • Monthly subscription-based licensing Pay for what you use and avoid upfront capital database management • Retain control with full database system (DBMS) expenditures. administrator (DBA) access of IBM hosted instance • Simplified administration You have full administrative control. Automatic provisioning, • Help protect your data with this advanced configuration and facilitated high availability disaster recovery security and single-tenant cloud platform (HADR) setup help lighten your workload. • Deploy IBM Db2 Hosted rapidly to • Deployment location flexibility over 30 IBM Cloud data centers around the world Help meet your data locality requirements and push data closer to where users need it by deploying to dozens of IBM Cloud data • Budget predictably with monthly centers around the world. subscription-based licensing IBM Analytics Data sheet IBM Db2 Hosted use cases IBM Db2 Hosted features The IBM Db2 solution offers the same functionality as its and configurations on-premises equivalent, so it’s equally suitable for transaction Fixed monthly fee with no hidden charges processing and analytics data workloads.