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Published By: Datastax     Published Date: Aug 03, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
Published By: Datastax     Published Date: Aug 07, 2018
Nobody likes being bogged down in operations, least of all database administrators who have enough to worry about already. The new DataStax Enterprise (DSE) has made it especially easy to be a DBA. With features like NodeSync, Advanced Replication, and OpsCenter, DSE is Apache Cassandra™ made simple. Read this white paper to learn how DSE simplifies your operations.
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Datastax
Published By: Datastax     Published Date: Aug 15, 2018
Nobody likes being bogged down in operations, least of all database administrators who have enough to worry about already. The new DataStax Enterprise (DSE) has made it especially easy to be a DBA. With features like NodeSync, Advanced Replication, and OpsCenter, DSE is Apache Cassandra™ made simple. Read this white paper to learn how DSE simplifies your operations.
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Datastax
Published By: Datastax     Published Date: Aug 15, 2018
Built on a production-certified version of Apache Spark™ and with integrated search and graph capabilities, DSE Analytics provides highly available, production-ready analytics that enables enterprises to securely build instantly responsive, contextual, always-on applications and generate ad-hoc reports. Read this white paper to learn about the specific features and capabilities of DSE Analytics, and why DSE Analytics is designed for the Right-Now Enterprise.
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Datastax
Published By: Datastax     Published Date: Aug 15, 2018
Today’s enterprises continue to differentiate themselves via their cloud applications. But differentiation is getting harder and harder to accomplish. To stand out, you need a flexible, nimble, scalable, always-on data platform that can deliver powerful, game-changing, customer-facing applications. Read this white paper to learn how DataStax Enterprise delivers comprehensive data management through a secure, operationally simple platform built on the best distribution of Apache Cassandra™.
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Datastax
Published By: Datastax     Published Date: Aug 15, 2018
Today’s companies require serious POWER at the data layer if they’re going to thrive in the Right-Now Economy. That’s why DataStax upped the ante with the latest version of its flagship product: DataStax Enterprise (DSE) 6. DSE 6 offers double the performance of DataStax Enterprise 5.1 and has now been independently verified as being at least twice as fast as open source Apache Cassandra. Read this white paper to learn all about DSE 6 performance improvements.
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Datastax
Published By: Datastax     Published Date: Aug 15, 2018
With DataStax Enterprise 6 (DSE 6), we upped the bar substantially for us, our partners, our customers, and our competitors. We also came out and said that DSE 6 was twice as fast as open source Apache Cassandra™, and now, we have a third-party validation of this claim. Read this benchmark report from zData to get the results of their test of DSE 6 against Cassandra, for which they ran a different series of workloads on an AWS-built cluster.
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Datastax
Published By: DataStax     Published Date: Mar 10, 2017
Netflix, Intuit and Clear Capital. These 3 innovative companies have one thing in common. They are altering their business landscape and transforming the way people live and work through highly personalized applications. And they're doing this with Apache Cassandra™ and DataStax. Download this white paper and learn why relational technologies failed to meet the demands of Netflix, Mint Bills and Clear Capital and how these enterprises modernize their Web and Mobile applications with DataStax to drive customer engagement, loyalty and lifetime value.
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DataStax
Published By: Red Hat     Published Date: Jan 01, 2009
The number 1 independent tire retailer tried, unsuccessfully, to build an online platform based on Windows. Ultimately, the company succeeded instead with a solution built with Red Hat Enterprise Linux, Red Hat Network Satellite, Apache, WebLogic, and IBM Lotus Domino Server.
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e-commerce business, red hat, satellite
    
Red Hat
Published By: Pure Storage     Published Date: Jan 12, 2018
Apache Spark has become a critical tool for all types of businesses across all industries. It is enabling organizations to leverage the power of analytics to drive innovation and create new business models. The availability of public cloud services, particularly Amazon Web Services, has been an important factor in fueling the growth of Spark. However, IT organizations and Spark users are beginning to run up against limitations in relying on the public cloud—namely control, cost and performance.
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data, storage, scalability, cost efficiencies, pure storage
    
Pure Storage
Published By: Teradata     Published Date: Jan 30, 2015
This report is about two of those architectures: Apache™ Hadoop® YARN and Teradata® Aster® Seamless Network Analytical Processing (SNAP) Framework™. In the report, each architecture is described; the use of each in a business problem is illustrated; and the results are compared.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, aster, snap, framework, apache, hadoop, yarn, architectures, data management, business technology
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, framework, apache, hadoop, architecture, warehouse, optimization, security, scalability, consistency, flexibility, data management
    
Teradata
Published By: Lucidworks     Published Date: Dec 14, 2016
You feel you’ve got a pretty good handle on the following challenges—exponentially increasing amounts of data, ever-increasing user expectations, and limited IT resources—along with your technical requirements. That’s why you chose to build your search app with Apache Solr. Download now to learn more about Apache SoIr and Lucidworks Fusion.
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Lucidworks
Published By: TIBCO Software APAC     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software APAC
Published By: IBM     Published Date: Feb 22, 2016
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage.
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ibm, data, big data, integration, hadoop, enterprise applications, data management, business technology
    
IBM
Published By: IBM     Published Date: Jul 14, 2016
This video describes how data scientists, analysts and business users can save precious time by using a combination of SPSS and Spark to uncover and act on insights in big data.
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ibm, data, analytics, predictive business, ibm spss, apache spark, coding, data science, software development, enterprise applications, data management, business technology, data center
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
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ibm, analytics, big data, hadoop, enterprise, ibm biginsights, apache, enterprise management, enterprise applications, data management, business technology, data science
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamlessly integrate with diverse technologies, from data marts to Apache Hadoop systems. And it must automatically discover, protect and monitor sensitive information as part of big data applications.
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IBM
Published By: IBM     Published Date: Apr 18, 2017
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data. To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
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data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
Known by its iconic yellow elephant, Apache Hadoop is purpose-built to help companies manage and extract insight from complex and diverse data environments. The scalability and flexibility of Hadoop might be appealing to the typical CIO but Aberdeen's research shows a variety of enticing business-friendly benefits.
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data management, yellow elephant, business benefits, information management
    
IBM
Published By: IBM APAC     Published Date: Aug 25, 2017
Machine learning automates the development of analytic models that can learn and make predictions on data. It has been one of the fastest growing disciplines within the world of statistics and data science, but the barrier to entry has been high, not only in cost, but also in the need for specialized talent.
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machine learning, apache spark, additional resources, big data, ibm
    
IBM APAC
Published By: IBM     Published Date: Jul 05, 2016
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
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ibm, analytics, big data, hadoop, enterprise, ibm biginsights, apache, enterprise management, knowledge management, enterprise applications, data management, data science, data storage, data visualization
    
IBM
Published By: IBM     Published Date: Oct 27, 2016
IBM Analytics for Apache Spark for Bluemix is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to other technologies on the market today. Optimized for extremely fast and large scale data processing-you can easily perform big data analysis from one application.
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ibm, apache spark, bluemix, analytics, enterprise applications, business technology, data science
    
IBM
Published By: IBM     Published Date: Nov 30, 2016
Learn how to create powerful analytic apps with IBM Cloudant, dashDB and Apache Spark. This presentation will contain demos of real-life use cases e.g. machine learning predictive analytics, Graph-parallel computation and more.
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ibm, cloud, analytic apps, apps, cloudant, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Nov 30, 2016
You’ve taken the first step and already know that a document- oriented database is the right database for your application. From here, you still have to decide where and how you’ll deploy the software and its associated infrastructure. These decisions lead to additional considerations around administrative overhead, technical support, open-source options, data sovereignty and security, and more. This paper aims to outline the deployment options available when you select IBM® Cloudant® as your JSON store.
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ibm, cloud, cloudant managed service, cloudant local, apache couchdb, enterprise applications, business technology
    
IBM
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