database model

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Published By: Group M_IBM Q3'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Security has become top of mind for CIOs, and CEOs. Encryption at rest is a piece of the solution, but not a big piece. Encryption over the network is another piece, but only a small piece. These and other pieces do not fit together well; they need to unencrypt and reencrypt the data when they move through the layers, leaving clear versions that create complex operational issues to monitor and detect intrusion. Larger-scale high-value applications requiring high security often use Oracle middleware, including Java and Oracle database. Traditional security models give the data to the processors to encrypt and unencrypt, often many times. The overhead is large, and as a result encryption is used sparingly on only a few applications. The risk to enterprises is that they may have created an illusion of security, which in reality is ripe for exploitation. The modern best-practice security model is an end-to-end encryption architecture. The application deploys application-led encryption s
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Oracle CX
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA
Published By: MarkLogic     Published Date: Jun 09, 2017
NoSQL means a release from the constraints imposed on database management systems by the relational database model. This quick, concise eBook provides an overview of NoSQL technology, when you should consider using a NoSQL database over a relational one (and when to use both). In addition, this book introduces Enterprise NoSQL and shows how it differs from other NoSQL systems. You’ll also learn the NoSQL lingo, which customers are already using it and why, and tips to find the right NoSQL database for you.
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MarkLogic
Published By: MarkLogic     Published Date: Jun 09, 2017
This eBook explains how databases that incorporate semantic technology make it possible to solve big data challenges that traditional databases aren’t equipped to solve. Semantics is a way to model data that focuses on relationships, adding contextual meaning around the data so it can be better understood, searched, and shared. Read this eBook, discover the 5 steps to getting smart about semantics, and learn how by using semantics, leading organizations are integrating disparate heterogeneous data faster and easier and building smarter applications with richer analytic capabilities.
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MarkLogic
Published By: CA Technologies     Published Date: Aug 24, 2017
• Use CA Live API Creator to deliver running prototypes in hours. Convert business requirements into working software. • Not just for wireframes, but also for running systems, databases, logic and user interfaces. It’s as simple as a spreadsheet and just as fast. • Impress your business users with results in hours to get their feedback on the data model and logic. Iterate instantly. • All you need is in the box. No IDE to install or configure. Just use your browser.
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CA Technologies
Published By: Oracle ODA     Published Date: Aug 15, 2016
Oracle added two new models to the Oracle Database Appliance family in addition to the existing high availability model. With an entry list price starting at a fourth of the cost of the prior generation Oracle Database Appliance hardware and flexible Oracle Database software licensing, these new models bring Oracle Engineered Systems to within reach of every organization. Read about how the Oracle Database Appliance X-6 series expands the reach of the database appliance family to support various workloads, deployment scenarios, and database editions. They are especially designed for customers requiring only single instance databases, but who desire the simplicity, optimization, and affordability of the Oracle Database Appliance. These new models are ideal for customers who seek to avoid the complexity, tuning requirements, and higher costs of “build-your-own” database solutions.
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Oracle ODA
Published By: Oracle     Published Date: Jan 28, 2019
For more than a decade, Oracle has developed and enhanced its ZFS Storage Appliance, giving its users a formidable unified and enterprise-grade storage offering. The latest release, ZS7-2, boasts upgraded hardware and software and is a timely reminder that more users might do well to evaluate this offering. It has a trifecta of advantages: (1) It’s notable performance, price-performance, and flexibility are all improved in this new release (2) There is a surprisingly inclusive set of functionalities, including excellent storage analytics that were developed even before analytics became a contemporary “must-have” (3) There’s a compelling group of “better together” elements that make ZFS Storage Appliance a particularly attractive choice for both Oracle Database environments and users that want to seamlessly integrate a cloud component into their IT infrastructure. Given the proven abilities of Oracle’s prior models, it’s also safe to assume that the new ZS7-2 will outperform other m
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Oracle
Published By: MarkLogic     Published Date: Mar 13, 2015
Big Data has been in the spotlight recently, as businesses seek to leverage their untapped information resources and win big on the promise of big data. However, the problem with big data initiatives are that organizations try using existing information management practices and legacy relational database technologies, which often collapse under the sheer weight of the data. In this paper, MarkLogic explains how a new approach is needed to handle the volume, velocity, and variety of big data because the current relational model that has been the status quo is not working. Learn about the NoSQL paradigm shift, and why NoSQL is gaining significant market traction because it solves the fundamental challenges of big data, achieving better performance, scalability, and flexibility. Learn how MarkLogic’s customers are reimagining their data to: - Make the world more secure - Provide access to valuable information - Create new revenue streams - Gain insights to increase market share - Reduce b
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enterprise, nosql, relational, databases, data storage, management system, application, scalable, data management
    
MarkLogic
Published By: MarkLogic     Published Date: Mar 17, 2015
You’ve probably heard about NoSQL, and you may wonder what it is. NoSQL represents a fundamental change in the way people think about storing and accessing data, especially now that most of the information generated is unstructured or semi-structured data — something for which existing database systems such as Oracle, MySQL, SQLServer, and Postgres aren’t well suited. NoSQL means a release from the constraints imposed on database management systems by the relational database model. This free eBook, Enterprise NoSQL for Dummies, MarkLogic Special Edition, provides an overview of NoSQL. You’ll start to understand what it is, what it isn’t, when you should consider using a NoSQL database instead of a relational database management system and when you may want to use both. In addition, this book introduces enterprise NoSQL and shows how it differs from other NoSQL systems, as well as explains when NoSQL may not be the right solution for your data storage problem. You’ll also learn the NoSQ
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enterprise, nosql, relational, databases, data storage, management system, application, scalable, data management
    
MarkLogic
Published By: Datastax     Published Date: Aug 23, 2017
Part of the “new normal” where data and cloud applications are concerned is the ability to handle multiple types of data models that exist in the application and persist each in a single datastore. This data management capability is called a “multi-model” database. Chances are you are getting bogged down by various data models that require support — key-value, tabular, JSON/document and graph. This not only raises your operational expenses, but also slows down your time to market and ultimately revenue growth. Download this free white paper and explore the multi-model concept, its rationale, and how DataStax Enterprise (DSE) is the only database that can help accelerate building and powering distributed, responsive and intelligent cloud applications across multiple data models.
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cloud, data model, multi-model
    
Datastax
Published By: Datastax     Published Date: Aug 27, 2018
"Part of the “new normal” where data and cloud applications are concerned is the ability to handle multiple types of data models that exist in the application and persist each in a single datastore. This data management capability is called a “multi-model” database. Download this free white paper and explore the multi-model concept, its rationale, and how DataStax Enterprise (DSE) is the only database that can help accelerate building and powering distributed, responsive and intelligent cloud applications across multiple data models"
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Datastax
Published By: MarkLogic     Published Date: Nov 07, 2017
Business demands a single view of data, and IT strains to cobble together data from multiple data stores to present that view. Multi-model databases, however, can help you integrate data from multiple sources and formats in a simplified way. This eBook explains how organizations use multi-model databases to reduce complexity, save money, lessen risk, and shorten time to value, and includes practical examples. Read this eBook to discover how to: Get unified views across disparate data models and formats within a single database Learn how multi-model databases leverage the inherent structure of data being stored Load as is and harmonize unstructured and semi-structured data Provide agility in data access and delivery through APIs, interfaces, and indexes Learn how to scale a multi-model database, and provide ACID capabilities and security Examine how a multi-model database would fit into your existing architecture
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MarkLogic
Published By: MarkLogic     Published Date: Nov 07, 2017
NoSQL means a release from the constraints imposed on database management systems by the relational database model. This quick, concise eBook provides an overview of NoSQL technology, when you should consider using a NoSQL database over a relational one (and when to use both). In addition, this book introduces Enterprise NoSQL and shows how it differs from other NoSQL systems. You’ll also learn the NoSQL lingo, which customers are already using it and why, and tips to find the right NoSQL database for you.
Tags : 
    
MarkLogic
Published By: MarkLogic     Published Date: Nov 07, 2017
This eBook explains how databases that incorporate semantic technology make it possible to solve big data challenges that traditional databases aren’t equipped to solve. Semantics is a way to model data that focuses on relationships, adding contextual meaning around the data so it can be better understood, searched, and shared. Read this eBook, discover the 5 steps to getting smart about semantics, and learn how by using semantics, leading organizations are integrating disparate heterogeneous data faster and easier and building smarter applications with richer analytic capabilities.
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MarkLogic
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas. Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
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total, cost, ownership, comparison, mongodb, oracle
    
AstuteIT_ABM_EMEA
Published By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
Tags : 
    
Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Security has become top of mind for CIOs, and CEOs. Encryption at rest is a piece of the solution, but not a big piece. Encryption over the network is another piece, but only a small piece. These and other pieces do not fit together well; they need to unencrypt and reencrypt the data when they move through the layers, leaving clear versions that create complex operational issues to monitor and detect intrusion. Larger-scale high-value applications requiring high security often use Oracle middleware, including Java and Oracle database. Traditional security models give the data to the processors to encrypt and unencrypt, often many times. The overhead is large, and as a result encryption is used sparingly on only a few applications. The risk to enterprises is that they may have created an illusion of security, which in reality is ripe for exploitation. The modern best-practice security model is an end-to-end encryption architecture. The application deploys application-led encryption s
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Oracle
Published By: Oracle     Published Date: Apr 03, 2012
This white paper describes how to successfully consolidate your database onto a private cloud through several deployment models.
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orace, service models, cloud management, 11g, database services, database consolidation
    
Oracle
Published By: CA Technologies EMEA     Published Date: May 23, 2018
To move your business from its current state to the connected enterprise, you have to define a common API to your database and other systems, while providing the infrastructure to support the new model. The new systems must incorporate the security safeguards while ensuring the infrastructure can support the new growing, but variable, load. With the rapid adoption of mobile and web-based services across the industry, the REST architecture has emerged as the de facto standard for API integration across systems. This white paper addresses the concepts of REST, creating REST APIs for your databases and integrating with other systems: • What is REST? • Why use REST for database access? • Building REST infrastructure for database access • The REST enabled database • Integrating REST with other services • Criteria for selecting REST services platform
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CA Technologies EMEA
Published By: Burton Group     Published Date: Jul 07, 2008
Data modeling has evolved from an arcane technique for database designers into an entire family of interrelated techniques that serves many constituencies, including techno-phobic business stakeholders and users. The new maturity of modeling tools and techniques arrives in the nick of time, because new technical and regulatory realities demand that enterprises maintain scrupulous awareness of their data and how it is used. Data modeling is no longer for databases only, no longer for technologists only, and no longer optional.
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modeling, data modeling, data management, data mining, business intelligence, dba, database administration, burton group
    
Burton Group
Published By: Oracle     Published Date: Apr 16, 2018
Lançado no Oracle Open World 2017, o Oracle Autonomous Database Cloud utiliza um revolucionário modelo de machine learning para habilitar a automação que elimina erros humanos e ajustes manuais, resultando em alto desempenho, disponibilidade de armazenamento e segurança a um custo muito mais baixo. Saiba como ele funciona e por que adotá-lo!
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proxima, geracao, banco, dados, lider, setor, acaba
    
Oracle
Published By: Oracle     Published Date: Apr 16, 2018
Oracle Autonomus Database Cloud, lanzada en el Oracle Open World 2017, usa un revolucionario modelo de machine learning que elimina el error humano y los ajustes manuales, para habilitar un alto rendimiento, seguridad y disponibilidad sin precedentes a un costo mucho más bajo. ¡Aprende cómo funciona y por qué adoptarlo!
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esta, aqui, nueva, generacion, bases, datos, lider, industria
    
Oracle
Published By: Datastax     Published Date: Apr 04, 2017
Graph databases are changing how we use data. But first, an example – you're (probably) a human working on a project and looking at graph databases as a potential solution. While we're a company that has a graph database that hopefully solves your problem. Now we could store that data in a boring relational database, but how do we do more than that? For instance, using that data, when combined with other data points, to find other people like you and recommend our solution to them? This is where a graph can come in handy. The friendly graph data model makes it easy to use patterns of relationships within large data sets. By leveraging those relationships we can analyze, or create better real-time experiences. Why Graph explores why this graph database 'thing' is really a thing, how they compare to other database systems, and the use cases they best support.
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graph, database, datastax
    
Datastax
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