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dbms

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Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
The relational database has been the foundation of enterprise data management for over thirty years. But the way we build and run applications today, coupled with unrelenting growth in new data sources and growing user loads are pushing relational databases beyond their limits. This can inhibit business agility, limit scalability and strain budgets, compelling more and more organizations to migrate to alternatives like MongoDB or NoSQL databases.
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rdbms, mongodb, migration, data, enterprise, management
    
AstuteIT_ABM_EMEA
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
Seit über 30 Jahren basiert die Datenverwaltung in Unternehmen auf relationalen Datenbanken. Doch die modernen Verfahren für die Entwicklung und den Betrieb von Anwendungen in Kombination mit der rasant steigenden Zahl neuer Datenquellen und den immer umfangreicheren Workloads der Anwender übersteigen zunehmend die Möglichkeiten relationaler Datenbanken. Die dadurch entstehenden Einschränkungen im Hinblick auf die Flexibilität und Skalierbarkeit sowie die steigenden finanziellen Belastungen bewegen mehr und mehr Unternehmen dazu, zu alternativen Datenbanken wie MongoDB oder NoSQL zu migrieren.
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leitfaden, fur, die, migration, von, einem, rdbms, mongodb
    
AstuteIT_ABM_EMEA
Published By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published By: Hewlett Packard Enterprise     Published Date: Aug 02, 2017
In midsize and large organizations, critical business processing continues to depend on relational databases including Microsoft® SQL Server. While new tools like Hadoop help businesses analyze oceans of Big Data, conventional relational-database management systems (RDBMS) remain the backbone for online transaction processing (OLTP), online analytic processing (OLAP), and mixed OLTP/OLAP workloads.
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database usage, database management, server usage, data protection
    
Hewlett Packard Enterprise
Published By: MarkLogic     Published Date: Jun 09, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic
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MarkLogic
Published By: Microsoft     Published Date: Oct 06, 2017
After rapid expansion of vendors and features, players in the operational DBMS market continue converging toward feature parity. Data and analytics leaders will be interested in the lack of Visionaries, competition in the Challengers quadrant and the maturing cloud capabilities among these vendors.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Microsoft
Published By: IBM     Published Date: May 17, 2016
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.
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ibm, intelligent business solutions, big data, transaction data, business analytics
    
IBM
Published By: MarkLogic     Published Date: Nov 08, 2016
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Download now to learn more.
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MarkLogic
Published By: MarkLogic     Published Date: Nov 07, 2017
Today, data is big, fast, varied and constantly changing. As a result, organizations are managing hundreds of systems and petabytes of data. However, many organizations are unable to get the most value from their data because they’re using RDBMS to solve problems they weren’t designed to fix. Why change? In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations are going beyond relational to embrace new kinds of databases. And when they do, the results can be dramatic.
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MarkLogic
Published By: Data Stax     Published Date: Apr 27, 2012
This paper examines key data management challenges facing modern businesses and explains how DataStax Enterprise provides the first post-relational database solution to handle real-time, analytic, and search data without using RDBMS solutions.
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datastax, data stax, data management, database management, database, enterprise, search data, rdbms
    
Data Stax
Published By: Oracle Global Marketing     Published Date: Jul 13, 2012
As the amount and importance of corporate data grows, companies of all sizes are finding that they increasingly need to deploy high-availability database solutions to support their business-critical applications.
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data, database, oracle database appliance, choosing hardware. storage, internal networking, memory, cpu, verify patch compatibility
    
Oracle Global Marketing
Published By: McAfee     Published Date: Feb 06, 2013
Protecting the valuable and confidential information stored within databases is vital for maintaining the integrity and reputation of organizations everywhere, and for ensuring regulatory compliance.
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vulnerability management, database security, dbms security, database activity monitoring, virtual patching, virtual patching for databases, virtualization
    
McAfee
Published By: McAfee     Published Date: Mar 08, 2013
Learn about McAfee Database Security solutions, compliance and security requirements, and principles for protecting your database.
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database security, native dbms auditing, sarbanes-oxley, pci dss, hipaa, sas 70, ssae 16, database compliance
    
McAfee
Published By: McAfee     Published Date: Mar 08, 2013
Compliance does not automatically equate to security. A company may be compliant with a host of regulatory requirements, while its databases remain exposed and vulnerable. Learn how McAfee Database Security can help prevent such vulnerabilities.
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database security, database compliance, native dbms auditing, database protection, database password audit, database activity monitoring, pci dss, sarbanes-oxley
    
McAfee
Published By: Vertica     Published Date: Dec 01, 2008
Cloud computing is ushering in a new era of analytic data management for business intelligence (BI) by enabling organizations to analyze terabytes of data faster and more economically than ever before. The key change: cloud database software is provisioned within minutes, without data center overhead, and it's licensed on an on-demand basis.
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vertica, ec2, elastic, cloud computing, ad-hoc, business intelligence, cloud, cloudbased applications
    
Vertica
Published By: Vertica     Published Date: Feb 01, 2010
How the Vertica Analytic Database is powering the new wave of commercial software, SaaS and appliance-based applications and creating new value and competitive differentiation for solution developers and their customers.
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vertica, ec2, cdr, elastic, saas, cloud computing, data management, ad-hoc
    
Vertica
Published By: Vertica     Published Date: Aug 16, 2010
The Vertica Analytic Database is the only database built from scratch to handle today's heavy business intelligence workloads. In customer benchmarks, Vertica has been shown to manage terabytes of data running on extraordinarily low-cost hardware and answers queries 50 to 200 times faster than competing row-oriented databases and specialized analytic hardware. This document summarizes the key aspects of Vertica's technology that enable such dramatic performance benefits, and compares the design of Vertica to other popular relational systems.
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vertica, ec2, elastic, cloud computing, workflow, benchmark, projections, ad-hoc
    
Vertica
Published By: Vertica     Published Date: Feb 20, 2010
For over a decade, IT organizations have been plagued by high data warehousing costs, with millions of dollars spent annually on specialized, high-end hardware and DBA personnel overhead for performance tuning. The root cause: using data warehouse database management (DBMS) software, like Oracle and SQLServer that were designed 20-30 years ago to handle write-intensive OLTP workloads, not query-intensive analytic workloads.
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vertica, ec2, cdr, elastic, saas, cloud computing, data management, ad-hoc
    
Vertica
Published By: Vertica     Published Date: Mar 15, 2010
Revenue assurance analysts at a top-tier US-based carrier studied this every day. Primarily focused on detecting fraud, revenue sharing contract violations and incomplete revenue collections, they had the need to query and analyze call detail record (CDR) databases that grow by millions of new CDRs every day.
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vertica, ec2, cdr, elastic, saas, dbms, sql, acid transactions
    
Vertica
Published By: Vertica     Published Date: Mar 15, 2010
In a world of growing data volumes and shrinking IT budgets, it is critical to think differently about the efficiency of your database and storage infrastructure. The Vertica Analytic Database is a high-performance, scalable and cost-effective solution that can bring dramatic savings in hardware, storage and operational costs.
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vertica, ec2, cdr, elastic, saas, cdr, cloud computing, data management
    
Vertica
Published By: Vertica     Published Date: Oct 30, 2009
Independent research firm Knowledge Integrity Inc. examine two high performance computing technologies that are transitioning into the mainstream: high performance massively parallel analytical database management systems (ADBMS) and distributed parallel programming paradigms, such as MapReduce, (Hadoop, Pig, and HDFS, etc.). By providing an overview of both concepts and looking at how the two approaches can be used together, they conclude that combining a high performance batch programming and execution model with an high performance analytical database provides significant business benefits for a number of different types of applications.
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vertica, analytical computing, adbms, mapreduce, application management, data management, data mining, grid computing
    
Vertica
Published By: Vertica     Published Date: Feb 23, 2010
Ovum takes a deep-dive technology audit of Vertica's Analytic Database that is designed specifically for storing and querying large datasets.
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ovum, vertica, analytical databases, dbms, technology audit, mpp, rdbms, grid computing
    
Vertica
Published By: Vertica     Published Date: Jul 23, 2008
Read how Comcast, the largest cable communications company in the U.S., is using Vertica Analytic DBMS able to quickly collect and analyze data being generated by millions of network devices to ensure quality of service and accuracy of capacity planning to ensure a consistently good customer experience.
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vertica, comcast, data analysis, proliant, rdmbs, networking, telecommunications, bandwidth management
    
Vertica
Published By: Vertica     Published Date: Jan 19, 2010
Pink OTC Market Inc. is the third largest U.S. equity trading marketing place. Learn how Pink OTC built a highly available and highly reliable (no downtime in a year of production use) data warehouse using Vertica's Analytic DBMS that cost-effectively stores billions of records and scales easily by simply adding CPUs without incurring additional licensing fees.
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pink, adr, data warehousing, vertica, dbms, database, analytical applications
    
Vertica
Published By: Vertica     Published Date: Dec 09, 2008
BlueCrest Capital Management is a leading European hedge fund, with $15B in assets-under-management. Learn how BlueCrest uses Vertica Analytic DBMS to obtain real-time analysis while simultaneously loading vast amounts of new market data.
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vertica, data management, data warehousing, dbms, data mining, data source, data, security
    
Vertica
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