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By: TIBCO     Published Date: Nov 09, 2015
As one of the most exciting and widely adopted open-source projects, Apache Spark in-memory clusters are driving new opportunities for application development as well as increased intake of IT infrastructure. Apache Spark is now the most active Apache project, with more than 600 contributions being made in the last 12 months by more than 200 organizations. A new survey conducted by Databricks—of 1,417 IT professionals working with Apache Spark finds that high-performance analytics applications that can work with big data are driving a large proportion of that demand. Apache Spark is now being used to aggregate multiple types of data in-memory versus only pulling data from Hadoop. For solution providers, the Apache Spark technology stack is a significant player because it’s one of the core technologies used to modernize data warehouses, a huge segment of the IT industry that accounts for multiple billions in revenue. Spark holds much promise for the future—with data lakes—a storage repo
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     TIBCO
By: GridGain     Published Date: Sep 24, 2014
In-memory computing (IMC) is an emerging field of importance in the big data industry. It is a quickly evolving technology, seen by many as an effective way to address the proverbial 3 V’s of big data—volume, velocity, and variety. Big data requires ever more powerful means to process and analyze growing stores of data, being collected at more rapid rates, and with increasing diversity in the types of data being sought—both structured and unstructured. In-memory computing’s rapid rise in the marketplace has the big data community on alert. In fact, Gartner picked in-memory computing as one of the Top Ten Strategic Initiatives.
Tags : gridgain, in memory computing, big data industry, 3v's of big data-volume
     GridGain
By: MEMSQL     Published Date: Apr 12, 2016
The pace of data is not slowing. Applications of today are built with infinite data sets in mind. As these real-time applications become the norm, and batch processing becomes a relic of the past, digital enterprises will implement memory-optimized, distributed data systems to simplify Lambda Architectures for real-time data processing and exploration.
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     MEMSQL
By: GridGain     Published Date: Mar 10, 2015
Software as a Service (SaaS) is a software distribution model in which applications are hosted by a vendor or service provider and made available to customers over the Internet. Instead of companies installing software on their own servers, known as the on premises distribution model, application software providers host the software in the cloud and charge customers according to the time they spend using the software, or based on a monthly or annual fee. SaaS is becoming increasingly popular, and as the industry develops, more and more companies are dropping older business models in favor of this rapidly evolving methodology.
Tags : gridgain, saas, saas perfomance and scalability, in memory computing, data fabric, paas for saas, data grid, real-time streaming, hadoop
     GridGain
By: Kx Systems     Published Date: Jan 16, 2015
?Kdb+ is a column-based relational database with extensive in-memory capabilities, developed and marketed by Kx Systems. Like all such products, it is especially powerful when it comes to supporting queries and analytics. However, unlike other products in this domain, kdb+ is particularly good (both in terms of performance and functionality) at processing, manipulating and analysing data (especially numeric data) in real-time, alongside the analysis of historical data. Moreover, it has extensive capabilities for supporting timeseries data. For these reasons Kx Systems has historically targeted the financial industry for trading analytics and black box trading based on real-time and historic data, as well as realtime risk assessment; applications which are particularly demanding in their performance requirements. The company has had significant success in this market with over a hundred major financial institutions and hedge funds deploying its technology. In this paper, however, we wa
Tags : kx systems, kdb+, relational database
     Kx Systems
By: snowflake     Published Date: Jun 09, 2016
Why Read This Report 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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     snowflake
By: Intel     Published Date: Sep 27, 2019
The stakes are high in today's data centers. Organisations have access to massive quantities of data promising valuable insights and new opportunities for business. But data center architects need to rethink and redesign their system architectures to ingest, store and process all that information. Similarly, application owners need to assess how they can process data more effectively. Those who don't re-architect might find themselves scrambling just to keep from being drowned in a data deluge.
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     Intel
By: Intel     Published Date: Sep 27, 2019
As data constantly changes and expands, data centers increasingly face capacity, performance, and cost limitations related to existing memory and storage solutions. Intel Optane data center (DC) technology addresses these challenges by placing data closer to the CPU and closing the gap between traditional memory and storage options, thus transforming the memory and storage tier.
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     Intel
By: Intel     Published Date: Sep 27, 2019
As the first major memory and storage breakthrough in 25 years, Intel Optane technology combines industry-leading low latency, high endurance, QoS, and high throughput that allows the creation of solutions to remove data bottlenecks, and unleash CPU utilization. With Intel Optane technology, data centers can deploy bigger and more affordable datasets to gain new insights from large memory pools. Here are just ten way Intel Optane technology can make a difference to your business. To find out more download this whitepaper today.
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     Intel
By: Intel     Published Date: Sep 30, 2019
Mountains of data promise valuable insights and innovation for businesses that rethink and redesign their system architectures. But companies that don’t re-architect might find themselves scrambling just to keep from being buried in the avalanche of data. The problem is not just in storing raw data, though. For businesses to stay competitive, they need to quickly and cost-effectively access and process all that data for business insights, research, artificial intelligence (AI), and other uses. Both memory and storage are required to enable this level of processing, and companies struggle to balance high costs against limited capacities and performance constraints. The challenge is even more daunting because different types of memory and storage are required for different workloads. Furthermore, multiple technologies might be used together to achieve the optimal tradeoff in cost versus performance. Intel is addressing these challenges with new memory and storage technologies that emp
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     Intel
By: Intel     Published Date: Sep 20, 2019
Skilled IT teams understand that one cloud does not fit all. Compliance issues may demand that some data be held internally. Budget-imposed total cost of ownership (TCO) limits may push other data out to public clouds. Hence, a scalable multi-cloud infrastructure becomes imperative. This whitepaper addresses key questions commonly raised by CIOs considering the move to multi-cloud. Further, it sheds light on how Intel® technologies such as the 2nd Generation Intel® Xeon® Scalable processors and Intel® Optane™ DC Persistent Memory can help boost your cloud credentials.
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     Intel
By: SAP     Published Date: Feb 03, 2017
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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     SAP
By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
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.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
By: SAP     Published Date: May 18, 2014
This white paper, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.
Tags : sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools
     SAP
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