enterprise database

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Published By: DATAVERSITY     Published Date: May 25, 2014
Deconstructing NoSQL: Analysis of a 2013 Survey on the Use, Production, and Assessment of NoSQL Technologies in the Enterprise This report examines the non-relational database environment from the viewpoints of those within the industry–whether current or future adopters, consultants, developers, business analysts, vendors, or others. This paper is sponsored by: MarkLogic, Cloudant and Neo4j.
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research paper, analysis, nosql, database, nosql database, white paper, nosql white paper
    
DATAVERSITY
Published By: Couchbase     Published Date: Dec 04, 2014
Interactive applications have changed dramatically over the last 15 years. In the late ‘90s, large web companies emerged with dramatic increases in scale on many dimensions: · The number of concurrent users skyrocketed as applications increasingly became accessible · via the web (and later on mobile devices). · The amount of data collected and processed soared as it became easier and increasingly · valuable to capture all kinds of data. · The amount of unstructured or semi-structured data exploded and its use became integral · to the value and richness of applications. Dealing with these issues was more and more difficult using relational database technology. The key reason is that relational databases are essentially architected to run a single machine and use a rigid, schema-based approach to modeling data. Google, Amazon, Facebook, and LinkedIn were among the first companies to discover the serious limitations of relational database technology for supporting these new application requirements. Commercial alternatives didn’t exist, so they invented new data management approaches themselves. Their pioneering work generated tremendous interest because a growing number of companies faced similar problems. Open source NoSQL database projects formed to leverage the work of the pioneers, and commercial companies associated with these projects soon followed. Today, the use of NoSQL technology is rising rapidly among Internet companies and the enterprise. It’s increasingly considered a viable alternative to relational databases, especially as more organizations recognize that operating at scale is more effectively achieved running on clusters of standard, commodity servers, and a schema-less data model is often a better approach for handling the variety and type of data most often captured and processed today.
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database, nosql, data, data management, white paper, why nosql, couchbase
    
Couchbase
Published By: MarkLogic     Published Date: Jun 17, 2015
Modern enterprises face increasing pressure to deliver business value through technological innovation that leverages all available data. At the same time, those enterprises need to reduce expenses to stay competitive, deliver results faster to respond to market demands, use real-time analytics so users can make informed decisions, and develop new applications with enhanced developer productivity. All of these factors put big data at the top of the agenda. Unfortunately, the promise of big data has often failed to deliver. With the growing volumes of unstructured and multi-structured data flooding into our data centers, the relational databases that enterprises have relied on for the last 40-years are now too limiting and inflexible. New-generation NoSQL (“Not Only SQL”) databases have gained popularity because they are ideally suited to deal with the volume, velocity, and variety of data that businesses and governments handle today.
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data, data management, databse, marklogic, column store, wide column store, nosql
    
MarkLogic
Published By: MapR Technologies     Published Date: Mar 29, 2016
Add Big Data Technologies to Get More Value from Your Stack Taking advantage of big data starts with understanding how to optimize and augment your existing infrastructure. Relational databases have endured for a reason – they fit well with the types of data that organizations use to run their business. These types of data in business applications such as ERP, CRM, EPM, etc., are not fundamentally changing, which suggests that relational databases will continue to play a foundational role in enterprise architectures for the foreseeable future. One area where emerging technologies can complement relational database technologies is big data. With the rapidly growing volumes of data, along with the many new sources of data, organizations look for ways to relieve pressure from their existing systems. That’s where Hadoop and NoSQL come in.
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MapR Technologies
Published By: Cloudant - an IBM Company     Published Date: Aug 01, 2015
The database you pick for your next web or mobile application matters now more than ever. Today’s applications are expected to run non-stop and must efficiently manage continuously growing amounts of transactional and multi-structured data in order to do so. This has caused NoSQL to grow from a buzzword to a serious consideration for every database, from small shops to the enterprise. Read this whitepaper to learn why NoSQL databases have become such a popular option, explore the various types available, and assess whether you should consider implementing a NoSQL solution for your next application.
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Cloudant - an IBM Company
Published By: Basho     Published Date: Sep 30, 2016
The Internet of Things (IoT) or the Internet of Everything is changing the way companies interact with their customers and manage their data. These connected devices generate high volume time series data that can be created in milliseconds. This fast growth of IoT data and other time series data is producing challenges for enterprise applications where data must be collected, saved, and analyzed in the blink of an eye. Your application needs a database built to uniquely handle time series data to ensure your data is continuously available and accurate.Learn about the only NoSQL database optimized for IoT and Time Series data in this technical overview. Riak TS stores and analyzes massive amounts of data and is designed to be faster than Cassandra.
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Basho
Published By: TD Bank Group     Published Date: Aug 10, 2018
This paper examines whether blockchain distributed ledger technology could improve the management of trusted information, specifically considering data quality. Improvement was determined by considering the impact of a distributed ledger as an authoritative source in TD Bank Group's Enterprise Data Quality Management Process versus the use of standard authoritative sources such as databases and files. Distributed ledger technology is not expected, or proven, to result in a change in the Data Quality Management process. Our analysis focused on execution advantages possible due to distributed ledger properties that make it an attractive resource for data quality management (DQM).
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TD Bank Group
Published By: graphgrid     Published Date: Oct 19, 2018
Graph databases are about to catapult across the famous technology adoption chasm and land in start-ups, enterprises and government agencies across the globe. The adoption antibodies are subsiding as the power of natively connected data becomes fundamental to any organization looking for data-driven insights across operations, suppliers, and customers. Moore’s Law increases in storage capacity and processing power can no longer keep up with the pace of data expansion, yet how companies structure and analyze their data ultimately will impact their ability to compete. Unstructured, disconnected data is useless. Graph databases will rapidly jump from niche use cases to a transformative IT technology as they enable turning the data you collect into actionable insights. Data will become the single most differentiating asset for your organization.
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graphgrid
Published By: Basho     Published Date: Nov 25, 2015
The landscape of Scalable Operational and Analytical Systems is changing and disrupting the norm of using relational databases for all workloads. With the growing need to process and analyze Big Data at Scale, the demand for alternative strategies has grown and has given rise to the emergence of NoSQL databases for scalable processing. Mike Ferguson, Managing Director of Intelligent Business Strategies, is an independent IT Analyst who specializes in Big Data, BI/Analytics, Data Management and Enterprise Business Integration. In this whitepaper he will discuss the movement towards NoSQL databases for scalable operational and analytical systems, what’s driving Big Data analytics from Hadoop to the emergence of Apache Spark, the value of operational analytics and the importance of in-memory processing, and why use Apache Spark as your in-memory analytical platform for operational analytics.
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Basho
Published By: birst     Published Date: Jan 21, 2013
This Dive Deep analyst report looks at the process of building an environment for what can be aptly termed Agile Business Analytics.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
birst
Published By: SAP     Published Date: Jan 23, 2013
This paper examines the root causes of data centralization failure and then reviews straightforward best practices that can help avoid such failures but are typically ignored when systems are designed in an ad hoc, organic manner.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
SAP
Published By: SAS     Published Date: Apr 02, 2014
Featuring use cases of various big data strategies, this paper explores several approaches and techniques that could be right for your enterprise, including using emerging big data platforms and creating new technology for problems not addressed by current big data platforms. It also covers moving more computation to traditional databases and implementing data virtualization.
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data, data management, big data, white paper, sas
    
SAS
Published By: Sqrrl Data, Inc.     Published Date: Jun 02, 2014
With the dissolution of the “trusted zone”, Data-Centric Security is a key enabler for Big Data applications. Sqrrl's Enterprise is a NoSQL database that is built with a Data-Centric Security implementation that includes cell-level security labeling and enforcement, encryption at rest, encryption in motion, an automated data labeling engine, a security policy specification engine, custom secure search indexing, and an audit facility.
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Sqrrl Data, Inc.
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
What if you could reduce the cost of running Oracle databases and improve database performance at the same time? What would it mean to your enterprise and your IT operations? Oracle databases play a critical role in many enterprises. They’re the engines that drive critical online transaction (OLTP) and online analytical (OLAP) processing applications, the lifeblood of the business. These databases also create a unique challenge for IT leaders charged with improving productivity and driving new revenue opportunities while simultaneously reducing costs.
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cost reduction, oracle database, it operation, online transaction, online analytics
    
Hewlett Packard Enterprise
Published By: Oracle CX     Published Date: Oct 19, 2017
Oracle has just announced a new microprocessor, and the servers and engineered system that are powered by it. The SPARC M8 processor fits in the palm of your hand, but it contains the result of years of co-engineering of hardware and software together to run enterprise applications with unprecedented speed and security. The SPARC M8 chip contains 32 of today’s most powerful cores for running Oracle Database and Java applications. Benchmarking data shows that the performance of these cores reaches twice the performance of Intel’s x86 cores. This is the result of exhaustive work on designing smart execution units and threading architecture, and on balancing metrics such as core count, memory and IO bandwidth. It also required millions of hours in testing chip design and operating system software on real workloads for database and Java. Having faster cores means increasing application capability while keeping the core count and software investment under control. In other words, a boost
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Oracle has just announced a new microprocessor, and the servers and engineered system that are powered by it. The SPARC M8 processor fits in the palm of your hand, but it contains the result of years of co-engineering of hardware and software together to run enterprise applications with unprecedented speed and security. The SPARC M8 chip contains 32 of today’s most powerful cores for running Oracle Database and Java applications. Benchmarking data shows that the performance of these cores reaches twice the performance of Intel’s x86 cores. This is the result of exhaustive work on designing smart execution units and threading architecture, and on balancing metrics such as core count, memory and IO bandwidth. It also required millions of hours in testing chip design and operating system software on real workloads for database and Java. Having faster cores means increasing application capability while keeping the core count and software investment under control. In other words, a boost
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Oracle CX
Published By: IBM     Published Date: Jun 29, 2018
IBM LinuxONE™ is an enterprise Linux server engineered to deliver cloud services that are secure, fast and instantly scalable. The newest member of the family, IBM LinuxONE Emperor™ II, is designed for businesses where the following may be required: • protecting sensitive transactions and minimizing business risk • accelerating the movement of data, even with the largest databases • growing users and transactions instantly while maintaining operational excellence • accessing an open platform that speeds innovation
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IBM
Published By: Oracle     Published Date: Aug 01, 2018
The Zero Data Loss Recovery Appliance’s benefits are compelling for any enterprise with a need to protect critical Oracle databases. The differences between this database recovery appliance and other approaches to data protection are stark. The Recovery Appliance leverages a combination of existing proven technologies and new developments that eliminate data loss and improve recovery. The elimination of periods between backups when database changes are not captured is also a major benefit, and the movement to a process of frequent or constant incremental backups provided by this appliance changes the game.
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Oracle
Published By: Oracle     Published Date: Aug 01, 2018
Your enterprise runs its critical applications on Oracle Databases, and as an enterprise IT leader, maintaining the performance and availability of your databases is among your top priorities. Any degradation in performance or loss of data could result in serious business disruption and loss of revenue, so protecting this vital asset is a must. There are many causes of data loss— administration errors, system or media failures, cyberattacks, and more—but we often overlook design flaws in the very systems meant to protect data: general-purpose backup systems.
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Oracle
Published By: Red Hat     Published Date: Jan 01, 2013
IT teams that need high-performing, secure database deployments are turning to Red Hat Enterprise Linux as a foundation for these deployments. Thorough testing and impressive results on industry-standard benchmarks make Red Hat Enterprise Linux a great candidate for operations ranging from high-performance computing to cloud infrastructure.
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performance, enterprise, database, workloads, red hat, high-performance computing, cloud infrastructure
    
Red Hat
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: IBM     Published Date: Sep 22, 2011
Companies need capabilities for identifying data assets and relationships, assessing data growth and implementing tiered storage strategies-capabilities that information governance can provide. It is important to classify enterprise data, understand data relationships and define service levels. Database archiving has proven effective in managing continued application data growth especially when it is combined with data discovery.
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ibm, application data, technology, enterprise, database archive, analytical applications, database development, data quality, database security
    
IBM
Published By: Datastax     Published Date: Jul 02, 2018
When you think enterprise ecommerce in the Right-Now Economy, you need to know that it all starts with a distributed cloud database built for hybrid cloud. From Safeway to eBay to Macy’s to Sony, leading companies across industries use DataStax to power their ecommerce initiatives. Read this ebook for a look into exactly how they use us and the results they’ve achieved.
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Datastax
Published By: Datastax     Published Date: Jul 02, 2018
In this eBook, we’ll take a look at why DataStax and Azure combine to make the ideal hybrid operational cloud database for the modern application needs of many of our large enterprise customers. The eBook explains how digital disruptors like Microsoft, Komatsu, and IHS Markit are leveraging the DSE+Azure hybrid cloud database to build game-changing applications built for the Right-Now Economy.
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Datastax
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