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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
    
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
    
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
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
Data matters more than ever to business success. But value does not come from data alone. Rather, it comes from the insights enabled by data. No matter what your role is, or where you are in your data journey, you are looking for ways to drive innovation.
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ibm, analytics, aps data, open data science, data science, apache spark
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
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.
Tags : 
ibm, cloud, analytics, cloudant managed service, cloudant local, apache couchdb, databases
    
IBM
Published By: Datastax     Published Date: Apr 04, 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, netflix, mint bills, digital, personalization
    
Datastax
Published By: Datastax     Published Date: Aug 23, 2017
Enterprises today continue to differentiate themselves with cloud applications – any application that needs to be always-on, distributed, scalable, real-time, and contextual. With DataStax Enterprise, DataStax delivers comprehensive data management with a unique always-on architecture that accelerates the ability of enterprises, government agencies, and systems integrators to power the exploding number of cloud applications. DataStax Enterprise (DSE) powers these cloud applications that require data distribution across data centers and clouds, by using a secure, operationally simple platform. At its core, DSE offers the industry’s best distribution of Apache Cassandra™. This paper provides a summary of the features and functionality of DataStax Enterprise that make it the best choice for companies that are looking to leverage the promise of Apache Cassandra™ for production environments.
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cloud, adoption, application, migration, performance
    
Datastax
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 27, 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 27, 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 27, 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 27, 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.
Tags : 
    
Datastax
Published By: Datastax     Published Date: Aug 28, 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™.
Tags : 
    
Datastax
Published By: Datastax     Published Date: Aug 28, 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.
Tags : 
    
Datastax
Published By: Datastax     Published Date: Aug 28, 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.
Tags : 
    
Datastax
Published By: Datastax     Published Date: Apr 08, 2019
For decades, organizations relied on traditional relational database management systems (RDBMS) to organize, store, and analyze their data. But then Facebook came along, and an RDBMS was suddenly not quite enough. The social giant needed a powerful database solution for its Inbox Search feature, and Apache Cassandra—a distributed NoSQL database—was born. Released as an open source project in July 2008, Cassandra—named after the mythological prophet who famously put a curse on an oracle—became an Apache Incubator project in March 2009. It graduated to a top-level project in February 2010
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Datastax
Published By: Datastax     Published Date: May 20, 2019
Apache Cassandra™ comes with the typical benefits of any NoSQL database, and much more. When enterprises need something easily scalable and ready for today’s hybrid cloud environments, it’s hard to find a database better suited for the job than Cassandra. From performance to availability to hybrid cloud readiness, this ebook explains the five main benefits of Cassandra.
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Datastax
Published By: Datastax     Published Date: May 20, 2019
Data management challenges have evolved drastically over the last decade, leading most companies to rethink how they manage their data. The need for more powerful and far more flexible databases resulted in the birth of the NoSQL database Apache Cassandra™. Read this white paper to learn how Cassandra has evolved and how it works.
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Datastax
Published By: Datastax     Published Date: Oct 11, 2019
The first and most important step to building a successful, scalable application is getting the data model right. In this white paper, you’ll get a detailed, straightforward, five-step approach to creating the right data model right out of the gate—from mapping workflows, to practicing query-first design thinking, to using Cassandra data types effectively.
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Datastax
Published By: Data Stax     Published Date: Apr 27, 2012
This paper examines those key characteristics and discusses how Apache Cassandra stacks up from an evaluation perspective.
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apache, datastax, data stax, cloud, cloud database, data management, database management, apache cassandra, evaluation
    
Data Stax
Published By: Intel     Published Date: Jun 22, 2015
Until recently, we used the Intel® Distribution for Apache Hadoop Software (IDH) to support our original three business intelligence (BI) big data use cases, and it delivered results worth millions of dollars to Intel.
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Intel
Published By: Hortonworks     Published Date: Apr 05, 2016
Download this whitepaper to learn how Hortonworks Data Platform (HDP), built on Apache Hadoop, offers the ability to capture all structured and emerging types of data, keep it longer, and apply traditional and new analytic engines to drive business value, all in an economically feasible fashion. In particular, organizations are breathing new life into enterprise data warehouse (EDW)-centric data architectures by integrating HDP to take advantage of its capabilities and economics.
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Hortonworks
Published By: Hortonworks     Published Date: Apr 05, 2016
This white paper will help you evaluate your ability to protect your data in a Apache Hadoop ecosystem. Read on to learn ten signs that you might need to improve security and data governance in order to manage risk while getting more value out of your Apache Hadoop environment.
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Hortonworks
Published By: BlueData     Published Date: Mar 13, 2018
In a benchmark study, Intel compared the performance of Big Data workloads running on a bare-metal deployment versus running in Docker containers with the BlueData software platform. This landmark benchmark study used unmodified Apache Hadoop* workloads
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big data, big data analytics, hadoop, apache spark, docker
    
BlueData
Published By: StreamSets     Published Date: Sep 24, 2018
If you’ve ever built real-time data pipelines or streaming applications, you know how useful the Apache Kafka™ distributed streaming platform can be. Then again, you’ve also probably bumped up against the challenges of working with Kafka. If you’re new to Kafka, or ready to simplify your implementation, we present common challenges you may be facing and five ways that StreamSets can make your efforts much more efficient and reliable
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apache, kafka, steam, sets, data
    
StreamSets
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