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database model

Results 1 - 25 of 38Sort Results By: Published Date | Title | Company Name
Published By: Group M_IBM Q3'19     Published Date: Sep 04, 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: Group M_IBM Q2'19     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 Q2'19
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 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: 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: Datastax     Published Date: Aug 27, 2018
Graph databases have the power to see deeply into real-time data relationships and make it easy to use relationship patterns for instant insight into large data sets. From IoT to networking to customer 360 to solving business problems with multi-model support, the power of graph can never be understated. Read this white paper to learn the uses cases for graph databases and how graph databases work.
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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: Datastax     Published Date: Aug 03, 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: 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: 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: Microsoft Azure     Published Date: Apr 11, 2018
When you extend the global reach of your enterprise, you’ll find new markets for your products and services. That means reaching more potential customers, bigger growth potential, and higher ROI. But to tap into those emerging markets, you need to provide the best, most consistent user experience. Now, it’s possible for you to build, deploy, and manage modern apps at scale with a globally-distributed database—without the hassles associated with hosting in your data center. Read the e-book Build Modern Apps with Big Data at a Global Scale and learn how Azure Cosmos DB, a globally-distributed turnkey database service, is transforming the world of modern data management. Keep access to your data available, consistent, and safe—with industry-leading, enterprise-grade security and compliance. Start developing the best app experience for your users based on five well-defined consistency models: Strong: Favors data consistency. Ideal for banks, e-commerce processing, and online booking. Boun
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Microsoft Azure
Published By: Microsoft Azure     Published Date: Apr 11, 2018
Developing for and in the cloud has never been more dependent on data. Flexibility, performance, security—your applications need a database architecture that matches the innovation of your ideas. Industry analyst Ovum explored how Azure Cosmos DB is positioned to be the flagship database of internet-based products and services, and concluded that Azure Cosmos DB “is the first to open up [cloud] architecture to data that is not restricted by any specific schema, and it is among the most flexible when it comes to specifying consistency.” From security and fraud detection to consumer and industrial IoT, to personalized e-commerce and social and gaming networks, to smart utilities and advanced analytics, Azure Cosmos DB is how Microsoft is structuring the database for the age of cloud. Read the full report to learn how a globally distributed, multi-model data service can support your business objectives. Fill out the short form above to download the free research paper.
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Microsoft Azure
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: 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.
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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: 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
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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 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: 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: 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: 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.
Tags : 
    
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.
Tags : 
    
MarkLogic
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