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Published By: Group M_IBM Q1'18     Published Date: Feb 14, 2018
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization.
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gartner, magic quadrant, data science platform, machine-learning
    
Group M_IBM Q1'18
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
Published By: StreamSets     Published Date: Sep 24, 2018
The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. One area that benefits from replatforming is the data warehouse. According to research firm Gartner, “starting in 2018, data warehouse managers will benefit from hybrid architectures that eliminate data silos by blending current best practices with ‘big data’ and other emerging technology types.” There’s undoubtedly a lot to ain by modernizing data warehouse architectures to leverage new technologies, however the replatforming process itself can be harder than it would at first appear. Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.
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replatforming, age, data, lake, apache, hadoop
    
StreamSets
Published By: Pure Storage     Published Date: Oct 09, 2018
Apache® Spark™ has become a vital technology for development teams looking to leverage an ultrafast in-memory data engine for big data analytics. Spark is a flexible open-source platform, letting developers write applications in Java, Scala, Python or R. With Spark, development teams can accelerate analytics applications by orders of magnitude
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Pure Storage
Published By: MemSQL     Published Date: Nov 15, 2017
Pairing Apache Kafka with a Real-Time Database Learn how to: ? Scope data pipelines all the way from ingest to applications and analytics ? Build data pipelines using a new SQL command: CREATE PIPELINE ? Achieve exactly-once semantics with native pipelines ? Overcome top challenges of real-time data management
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digital transformation, applications, data, pipelines, management
    
MemSQL
Published By: WANdisco     Published Date: Oct 15, 2014
In this Gigaom Research webinar, the panel will discuss how the multi-cluster approach can be implemented in real systems, and whether and how it can be made to work. The panel will also talk about best practices for implementing the approach in organizations.
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wandisco, wan, wide area network, hadoop, clusters, clustering, load balancing, data, big data, data storage, storage
    
WANdisco
Published By: Splunk     Published Date: Sep 10, 2018
The financial services industry has unique challenges that often prevent it from achieving its strategic goals. The keys to solving these issues are hidden in machine data—the largest category of big data—which is both untapped and full of potential. Download this white paper to learn: *How organizations can answer critical questions that have been impeding business success *How the financial services industry can make great strides in security, compliance and IT *Common machine data sources in financial services firms
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cloud monitoring, aws, azure, gcp, cloud, aws monitoring, hybrid infrastructure, distributed cloud infrastructures, reduce mttr/mtti, cloud monitoring free, cloud monitoring tools, cloud monitoring service, cloud billing monitoring, cloud monitoring architecture, cloud data monitoring, host monitoring, *nix, unix, linux, servers
    
Splunk
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: IBM     Published Date: Feb 03, 2016
The more real-time and granular your data is, the more responsive and competitive your organization can become.
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ibm, data management, apache, hadoop, analytics, data science, data visualization, data security
    
IBM
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: 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: 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: MemSQL     Published Date: Nov 15, 2017
FREE O'REILLY EBOOK: BUILDING REAL-TIME DATA PIPELINES Unifying Applications and Analytics with In-Memory Architectures You'll Learn: - How to use Apache Kafka and Spark to build real-time data pipelines - How to use in-memory database management systems for real-time analytics - Top architectures for transitioning from data silos to real-time processing - Steps for getting to real-time operational systems - Considerations for choosing the best deployment option
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hardware trends, data pipelines, database management, architectures, technology
    
MemSQL
Published By: Nginx     Published Date: Jul 15, 2014
Users demand fast application delivery and it is essential for the survival of your business. Meeting the expectations of your users is challenging. NGINX Plus offers a broad array of solutions to solve these challenges, allowing you to delight your users.
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nginx, application delivery, web servers, application infrastructure, apache http server, high availability, load balancing, server performance, enterprise infrastructure, application performance, riverbed, reverse proxy, server software, web applications, enterprise software, it management, enterprise applications
    
Nginx
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: 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: IBM     Published Date: Jun 07, 2016
Once you know that a document oriented database is the best database for your application, you will have to decide where and how you'll deploy the software and its associated infrastructure. Download this white paper for an outline of the deployment options available when you select IBM® Cloudant® as your JSON store.
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ibm, cloudant managed service, cloudant local, apache couchdb, networking, enterprise applications, data management, 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
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.
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ibm, cloud, analytics, cloudant managed service, cloudant local, apache couchdb, databases, enterprise applications, data science, data storage
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
Watch to learn how an enterprise-grade, multi-tenant solution can help you deploy Spark in a production environment to take advantage of · Faster time-to-results for big data analytics · Simplified deployment and management · Increased utilization of hardware resources"
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ibm, analytics, production environment, apache spark, idc research, software development, enterprise applications, data management, business technology
    
IBM
Published By: Altiscale     Published Date: Oct 19, 2015
In this age of Big Data, enterprises are creating and acquiring more data than ever before. To handle the volume, variety, and velocity requirements associated with Big Data, Apache Hadoop and its thriving ecosystem of engines and tools have created a platform for the next generation of data management, operating at a scale that traditional data warehouses cannot match.
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big data, analytics, nexgen, hadoop, apache, networking
    
Altiscale
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 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 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™.
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Datastax
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