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database model

Results 1 - 25 of 38Sort Results By: Published Date | Title | Company Name
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: Basho     Published Date: Apr 07, 2015
This whitepaper looks at why companies choose Riak over a relational database. We focus specifically on availability, scalability, and the key/value data model. Then we analyze the decision points that should be considered when choosing a non-relational solution and review data modeling, querying, and consistency guarantees. Finally, we end with simple patterns for building common applications in Riak using its key/value design, dealing with data conflicts that emerge in an eventually consistent system, and discuss multi-datacenter replication.
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basho, riak, relational database, nosql, common applications, simple deployments, it management
    
Basho
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: 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: 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: 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
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 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: 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: Five9     Published Date: Apr 29, 2013
NJ 2-1-1 is a free phone number and online database that connects New Jersey residents quickly and effectively to community resources and emergency information. It is part of a growing national model that provides 190 million Americans in all 50 states.
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five9, cloud, cloud computing, cloud-based contact center, contact center software, hurricane sandy, networking, data center
    
Five9
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: 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: IBM     Published Date: Jun 07, 2016
The database you pick for your next application matters now more than ever. It can be difficult, and oftentimes impossible, to quickly join today's data into the relational model. Learn how a NoSQL database can act as a viable alternative to or compliment an existing relational database.
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ibm, nosql database, database, analytics, networking, enterprise applications
    
IBM
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
    
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
    
MarkLogic
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: 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: 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: Objectivity     Published Date: Aug 21, 2009
As business users expand to newer types of applications, and grow older ones, their attempts to use RDBMS encounter the "Relational Wall," where RDBMS technology no longer provides the performance and functionality needed. This paper measures the wall, explains what model and architectural differences cause it, how to foresee it, and how to avoid it.
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database, rdbmss, object, object-oriented, object oriented, database performance, database development, database architecture
    
Objectivity
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