memory

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Published By: Rohde & Schwarz Cybersecurity     Published Date: Nov 28, 2017
DPI software is made to inspect packets at high wire speeds and a critical factor is the throughput and resources required. Keeping the amount of resources that integrated DPI and application classification technology requires low is critical. The fewer cores (on a multi-core processor) and the less on-board memory an engine needs, the better. Multi-threading provides almost linear scalability on multi-core systems. In addition, highly-optimized flow tracking is required for handling millions of concurrent subscribers.
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detection, rate, performance, efficiency, accuracy, encrypted apps, integration, metadata
    
Rohde & Schwarz Cybersecurity
Published By: TE Connectivity     Published Date: Feb 07, 2018
Our free solutions guide features all of our dependable connectivity solutions for data & power. You’ll get 1. Data Communications Product Guide 2. Standard Flexible Printed Circuit (FPC) Connectors Quick Reference Guide 3. Memory Sockets Quick Reference Guide 4. Stacking Height Guide for Parallel Board-to-Board Applications 5. RF Connectors Quick Reference Guide 6. High Speed Input/Output Solutions Quick Reference Guide 7. AMPLIMITE Subminiature D Connectors Catalog 8. Soft Shell Pin & Socket Connectors Catalog
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TE Connectivity
Published By: Mimecast ABM Q4     Published Date: Nov 22, 2017
Mimecast Cloud Archive has long set the industry standard for enterprise information archiving, helping to keep corporate knowledge available, protecting and preserving it while simplifying management and administration. By aggregating data across multiple platforms, organizations gain long-term business insights and create a secure, digital corporate memory while at the same time reducing costs and risks for legal and compliance teams. IT teams can reduce administrative overhead with streamlined management and simplified data recovery. Anytime, anywhere access to archive data improves employee productivity and efficient workflow efficiency. Customers can rest assured that their data is always-available, always-replicated and always-safe.
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datenarchivierung, verantwortlich, eigentlich, organisation, it-mitarbeitern, wissensarbeiter, fuhrungsebene
    
Mimecast ABM Q4
Published By: Oracle     Published Date: Oct 20, 2017
Oracle has just announced a new microprocessor, and the servers and engineered system that are powered by it. The SPARC M8 processor fits in the palm of your hand, but it contains the result of years of co-engineering of hardware and software together to run enterprise applications with unprecedented speed and security. The SPARC M8 chip contains 32 of today’s most powerful cores for running Oracle Database and Java applications. Benchmarking data shows that the performance of these cores reaches twice the performance of Intel’s x86 cores. This is the result of exhaustive work on designing smart execution units and threading architecture, and on balancing metrics such as core count, memory and IO bandwidth. It also required millions of hours in testing chip design and operating system software on real workloads for database and Java. Having faster cores means increasing application capability while keeping the core count and software investment under control. In other words, a boost
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
The Software in Silicon design of the SPARC M7 processor, and the recently announced SPARC S7 processor, implement memory access validation directly into the processor so that you can protect application data that resides in memory. It also includes on-chip Data Analytics Accelerator (DAX) engines that are specifically designed to accelerate analytic functions. The DAX engines make in-memory databases and applications run much faster, plus they significantly increase usable memory capacity by allowing compressed databases to be stored in memory without a performance penalty. The following Software in Silicon technologies are implemented in the SPARC S7 and M7 processors: Note: Security in Silicon encompasses both Silicon Secured Memory and cryptographic instruction acceleration, whereas SQL in Silicon includes In-Memory Query Acceleration and In-Line Decompression. Silicon Secured Memory is the first-ever end-to-end implementation of memory-access validation done in hardware. It
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Oracle’s new cloud platform, included a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in memory and can prevent hacking explo
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
On Thursday June 30th, we announced Oracle’s new cloud platform, including a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
On Thursday June 30th, we announced Oracle’s new cloud platform, including a new line of servers for cloud and scale-out applications: Oracle’s SPARC S7-2 and S7-2L servers. These servers are based on the breakthrough SPARC S7 processor and extend the outstanding features and capabilities of the SPARC T7 and M7 systems into scale-out form factors. With the combination of Oracle’s breakthrough Software in Silicon features and the efficiency of the SPARC S7 processor we can offer the most secure and economical enterprise clouds with the fastest infrastructure for data analytics. Here at Oracle we recognize our customers’ needs for increasing the security of their data, therefore we have taken security as one of the core values on the SPARC Servers. The new SPARC S7 processor leverages the revolutionary Security in Silicon features introduced on the SPARC T7 and M7 systems. Silicon Secured Memory is a unique hardware implementation that prevents unauthorized access to application data in
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Oracle has just announced a new microprocessor, and the servers and engineered system that are powered by it. The SPARC M8 processor fits in the palm of your hand, but it contains the result of years of co-engineering of hardware and software together to run enterprise applications with unprecedented speed and security. The SPARC M8 chip contains 32 of today’s most powerful cores for running Oracle Database and Java applications. Benchmarking data shows that the performance of these cores reaches twice the performance of Intel’s x86 cores. This is the result of exhaustive work on designing smart execution units and threading architecture, and on balancing metrics such as core count, memory and IO bandwidth. It also required millions of hours in testing chip design and operating system software on real workloads for database and Java. Having faster cores means increasing application capability while keeping the core count and software investment under control. In other words, a boost
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Oracle
Published 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
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
Published 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.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management
    
SAP
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