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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, enterprise applications, data management
    
MarkLogic
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Today, as IT departments struggle to design and implement solutions capable of managing exponential data growth with strict requirements for application scale and performance, many of them are turning to in-memory data grids (IMDGs).
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it departments, data growth, managing data growth, application scale, application performance, in-memory data grids, imdgs, big data, data volume, data velocity, data variability, data management, data collection, data processing, data scaling, data storage systems, data access, data solutions, data challenges, management tooling
    
Red Hat, Inc.
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Is data changing the way you do business?Is it inventory sitting in your warehouse? The good news is data-driven applications enhance online customer experiences, leading to higher customer satisfaction and retention, and increased purchasing.
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it planning, data, data-driven applications, data challenges, data solutions, big data solutions, big data challenges, in-memory databases, web-abpplications, in-memory data grid, nosql, storage nodes, e-commerce applications, social applications, logisitcs applications, trading applications, data scaling, rest, memcached, hot rod
    
Red Hat, Inc.
Published By: OpTier     Published Date: Mar 11, 2013
In the Information Technology (IT) industry, 2012 has been the year of Big Data. From a standing start toward the end of the last decade, Big Data has become one of the most talked about topics.
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optier, big data, enterprise data warehouse, edw, nosql
    
OpTier
Published By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
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evolution, big data, technology, datastax, nosql
    
Datastax
Published By: SnowFlake     Published Date: Jul 08, 2016
In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
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forrester, enterprise, data, technology, best practices, innovation, security, business intelligence
    
SnowFlake
Published By: Pentaho     Published Date: Jan 16, 2015
Download if you need to make decisions about the architecture of the systems you work on. Sponsored by Pentaho.
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embedded, big data, nosql, hadoop, customer analytics, data integration, data delivery, data management, business intelligence, data center
    
Pentaho
Published By: IBM     Published Date: May 02, 2014
This paper introduces you to Big SQL, answering many of the common questions that relational database management system (DBMS) users have about this IBM technology.
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ibm, big data, big sql, querying data, database management technology, apache hadoop, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, it management, best practices, change management
    
IBM
Published By: IBM     Published Date: May 28, 2014
The ability to keep pace with trends like big data, open data, sophisticated analytics, and the de-compartmentalization of data silos and processes, distinguishes leading master data management (MDM) solutions from their counterparts. IBM, one of the five vendors in this evaluation, is positioned as THE leader with the most prominent, widely implemented solution in the market.
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ibm, forrester, master data management, big data, database management technology, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, data persistence, virtualize data, lifecycle management, big data strategy, it management, data management, data center
    
IBM
Published By: IBM     Published Date: Mar 05, 2014
If you specialize in relational database management technology, you’ve probably heard a lot about “big data” and the open source Apache Hadoop project. Perhaps you’ve also heard about IBM’s new Big SQL technology, which enables IBM® InfoSphere® BigInsights™ users to query Hadoop data using industry-standard SQL. Curious? This paper introduces you to Big SQL, answering many of the common questions that relational database management system (DBMS) users have about this IBM technology.
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ibm, big data, ibm big sql, sql, database management, database management technology, software, tables, queries, data platform, big sql architecture, programming language, relational database management system, rdbms, database development, analytical applications, business intelligence, data warehousing
    
IBM
Published By: Basho     Published Date: Apr 13, 2015
Today’s consumers expect instant access to communications services whether they’re in the office, at home, or on the road. With data speeds increasing and international roaming costs decreasing, data usage is rapidly growing. Telecommunications Service Providers (TSPs) are under pressure to deliver more services to more people and approach 100% uptime all while lowering prices to consumers. Traditional relational databases can’t meet the requirements for massive scalability, availability, and fault tolerance that the rapid growth in data usage and rise of big data demands. Read this solution brief to learn how Riak excels at these. Riak is a distributed NoSQL database optimized for big data. Riak meets many of the challenges you may be facing with your own service operations systems.
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riak, basho, telecommunications service provider, license fees, scalability, availability, data usage, big data, service operations system, networking, security, it management, wireless, data management
    
Basho
Published By: IBM     Published Date: Apr 29, 2015
IBM InfoSphere BigInsights for Hadoop enables organizations to efficiently manage and mine large volumes of diverse data for valuable insights. IBM builds on a 100% Apache Hadoop foundation with common tools such as spreadsheets, R analytics and SQL access for greater usability.
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bigsheets, data management, business intelligence, workload optimization, data, sql, network management, network performance, network provisioning, database development, productivity
    
IBM
Published By: HP     Published Date: Aug 26, 2014
HP Simply StoreIT takes the stress out of storage. HP and our network of over 200,000 channel partners worldwide can help you choose the right solutions to fit your biggest business challenges. We can help you overcome obstacles including too little time for managing IT, budgets for upgrading infrastructure, and too many business risks and threats. Now you can take charge of virtualization, storage for business solutions such as Exchange and SQL Server, growing file shares, and data protection for business continuity. Improve your operational efficiency, reduce your risks, and lower storage costs. See how.
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storage, budgets, server, virtualization, file, data, business, technology, portfolio, cloud-based, support, portal, solution, consolidate, islands, access, reliable, retention, protection, guesswork
    
HP
Published By: IBM     Published Date: Jun 10, 2014
Download this short paper for an overview of the benchmark, the result and understand the importance to businesses deploying Hadoop into their data warehouse environments.
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ibm, big sql, hadoop, sql, database development, application integration, data integration, data warehousing
    
IBM
Published By: IBM     Published Date: Nov 13, 2014
This paper focuses on the benefits of a queryable data store and big data technologies available to support data warehouse modernization. Read the paper to understand how data can be stored and optimized with Hadoop.
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ibm, ibm infosphere, big data, hadoop, big sql, data warehousing, storage management, analytical applications, data deduplication
    
IBM
Published By: Progress Software     Published Date: Mar 12, 2014
For IT managers, choosing the wrong vendor can lead to disruption, high costs, and the loss of confidence from within the business. Learn how to de-risk your vendor selections by aligning with market trends.
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progress software, choosing vendors, datadirect, connectivity, saas applications, big data, data warehousing, nosql, newsql, and non-relational databases, networking, software development, it management, data management, data center
    
Progress Software
Published By: Pentaho     Published Date: Jan 16, 2015
If you’re considering a big data project, this whitepaper provides an overview of current common use cases for big data, from entry-level to more complex. You’ll get an in-depth look at some of the most common, including data warehouse optimization, streamlined data refinery, monetizing your data, and getting a 360 degree view of your customer. For each, you’ll discover why companies are investing in them, what the projects look like, and key project considerations, including tools and platforms.
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big data, nosql, hadoop, data integration, data delivery, data management, data center
    
Pentaho
Published By: IBM     Published Date: May 02, 2014
Learn more about Forrester’s results, and how these organizations are realizing both economic and operational benefits with InfoSphere Optim solutions.
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ibm, big data, big sql, querying data, database management technology, apache hadoop, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, data persistence, virtualize data, lifecycle management, big data strategy, it management, data management
    
IBM
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