databases

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Published By: AWS     Published Date: Jul 25, 2019
What you'll learn in this webinar: Simplify the move from legacy commercial databases or niche database solutions to Amazon Web Services (AWS) with help from experts in database migration and automation software solutions from mLogica. Watch our webinar to hear how you can transform your legacy environment to an AWS cloud-native infrastructure by migrating to Amazon Aurora. Using mLogicas fully automated, self-learning mLogica Database Migration Studio, and consultancy service, you can modernize your databases and applications without disrupting your daily operations. Join our webinar to learn how: mLogica helped TicketSocket unify and simplify its data and gain efficiencies of cost and scale You can move enterprise, mission-critical complex databases to AWS You can break free of commercial licensing obligations
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AWS
Published By: CloudHealth by VMware     Published Date: Feb 13, 2019
Choosing Azure revolutionizes your environment's agility, simplicity, and innovation, but have you achieved the cost savings you expected? Discover 10 ways you can reduce your spend in Azure, including: -Terminate Zombie Assets -Delete Aged Snapshots -Rightsize Virtual Machines -Rightsize SQL Databases Read 10 Best Practices for Reducing Spend in Azure, to learn key strategies for optimizing cloud spend and saving 10-20% on your monthly Azure costs.
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cloud management, microsoft azure, multicloud management
    
CloudHealth by VMware
Published By: CloudHealth by VMware     Published Date: Apr 15, 2019
Choosing Azure revolutionises your environment's agility, simplicity, and innovation, but have you achieved the cost savings you expected? Discover 10 ways you can reduce your spend in Azure, including: Terminate Zombie Assets Delete Aged Snapshots Rightsize Virtual Machines Rightsize SQL Databases Read 10 Best practices for Reducing Spend in Azure, to learn key strategies for optimising cloud spend and saving 10-20?% on your monthly Azure costs.
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CloudHealth by VMware
Published By: StreamSets     Published Date: Sep 24, 2018
Treat data movement as a continuous, ever-changing operation and actively manage its performance. Before big data and fast data, the challenge of data movement was simple: move fields from fairly static databases to an appropriate home in a data warehouse, or move data between databases and apps in a standardized fashion. The process resembled a factory assembly line.
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practices, modern, data, performance
    
StreamSets
Published By: Progress Software     Published Date: Mar 12, 2014
For IT managers, choosing the wrong vendor can lead to disruption, high costs, and the loss of confidence from within the business. Learn how to de-risk your vendor selections by aligning with market trends.
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progress software, choosing vendors, datadirect, connectivity, saas applications, big data, data warehousing, nosql
    
Progress Software
Published By: Blue Medora     Published Date: Oct 24, 2016
a recent Forrester Consulting research report shows that tools creep and lack of visibility are big problem areas for companies. Additionally, the research showed that only 24 percent of companies could provision infrastructure in a matter of hours instead of days or weeks.
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it operations, blue medora, visibility, cloud management, open-source databases, infrastructure provisioning
    
Blue Medora
Published By: Scalebase     Published Date: Mar 08, 2013
Technology analyst firm 451 Research offers a brief overview of ScaleBases Data Traffic Manager software for dramatic scaling of MySQL databases beyond the capabilities of MySQL 5.6.
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shard, cluster, high availability, failover, mariadb, mysql, read/write, scalability
    
Scalebase
Published By: McAfee     Published Date: Mar 08, 2013
McAfee Vulnerability Manager for Databases automatically discovers networked databases; determines if the latest patches have been applied; and tests for common weaknesses, making it easier to demonstrate compliance and better protect critical data.
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database security, database vulnerability manager, database compliance, mysql security, database password security, sql injection, buffer overflow, insecure sql code
    
McAfee
Published By: IBM     Published Date: Jun 21, 2017
There are many types of databases and data analysis tools to choose from when building your application. Should you use a relational database? How about a key-value store? Maybe a document database? Is a graph database the right ft? What about polyglot persistence and the need for advanced analytics? If you feel a bit overwhelmed, dont worry. This guide lays out the various database options and analytic solutions available to meet your apps unique needs. Youll see how data can move across databases and development languages, so you can work in your favorite environment without the friction and productivity loss of the past.
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data analysis, key value, document database, analytics
    
IBM
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas. Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
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total, cost, ownership, comparison, mongodb, oracle
    
AstuteIT_ABM_EMEA
Published By: Hewlett Packard Enterprise     Published Date: Sep 25, 2017
Solid state storage is increasingly deployed in all sizes of datacenters, from the small and medium business to the large enterprise. It comes in many forms including hybrid arrays, direct attached drives, PCIe flash and accelerators that fit somewhere in between servers and storage. With the price of flash continuing to drop, hybrid storage is becoming more compelling to the small and medium business for critical computing applications such as databases and day-to-day operational computing.
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Hewlett Packard Enterprise
Published By: IBM APAC     Published Date: Apr 27, 2018
While relying on x86 servers and Oracle databases to support their stock trading systems, processing rapidly increasing number of transactions fast became a huge challenge for Wanlian Securities. They shifted to IBM FlashSystem that helped them cut average response time for their Oracle Databases from 10 to less than 0.4 milliseconds and improved CPU usage by 15%. Download this case study now.
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IBM APAC
Published By: NexGen     Published Date: Feb 09, 2015
The nature of the financial services industry places a myriad of international compliance requirements on a company's IT team, as well as an expectation by its customers to deliver the high test levels of performance and reliability. To survive and thrive, businesses in the industry must not only keep pace with customer demand but gain competitive advantage. Those demands mean the IT team must be at the forefront of adopting emerging technologies. This is certainly true for Orangefield Columbus, who recently experienced significant growth in its multiple databases which led to the serious performance degradation of its existing storage system. By focusing on a proactive data management storage array, Orangefield was able to eliminate resource contention. Download now and examine Orangefield's journey to find a solution that would meet, and exceed, their performance and capacity requirements.
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nexgen, vmware, citrix, flash, financial services, it management
    
NexGen
Published By: Box     Published Date: Jan 16, 2015
The nature of the financial services industry places a myriad of international compliance requirements on a company's IT team, as well as an expectation by its customers to deliver the high test levels of performance and reliability. To survive and thrive, businesses in the industry must not only keep pace with customer demand but gain competitive advantage. Those demands mean the IT team must be at the forefront of adopting emerging technologies. This is certainly true for Orangefield Columbus, who recently experienced significant growth in its multiple databases which led to the serious performance degradation of its existing storage system. By focusing on a proactive data management storage array, Orangefield was able to eliminate resource contention. Download now and examine Orangefield's journey to find a solution that would meet, and exceed, their performance and capacity requirements.
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nexgen, vmware, citrix, flash, financial services, it management
    
Box
Published By: IBM     Published Date: Mar 29, 2017
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases including relational data warehouses is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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cloud, analytics, data, organization, ibm
    
IBM
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases including relational data warehouses is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases including relational data warehouses is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
One of the biggest changes faces organizations making purchasing and deployment decisions about analytic databases -- including relational data warehouses -- is whether to opt for a cloud solution.
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Group M_IBM Q2'19
Published By: McAfee     Published Date: Mar 07, 2013
McAfee delivers a complete database security solution that protects your entire database environment efficiently and cost effectively, while maintaining optimum system performance and availability.
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database security, database security compliance, database activity monitoring, virtual patching for databases, database compliance audit, database regulatory compliance, database vulnerability management, database vulnerabilities
    
McAfee
Published By: McAfee     Published Date: Mar 08, 2013
McAfee delivers a complete database security solution that protects your entire database environment efficiently and cost effectively, while maintaining optimum system performance and availability.
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database security, database security compliance, database activity monitoring, virtual patching for databases, database compliance audit, database regulatory compliance, database vulnerability management, database vulnerabilities
    
McAfee
Published By: Epson     Published Date: May 14, 2018
Consumers worldwide continue to adopt and use technology in their shopping experience. Faced with rising customer expectations and increasing competitive pressures, retailers now are prioritizing in-store innovation. Many retailers have adopted multichannel implementations, in which mobile, web, and in-store shopping are enabled but not delivered consistently to the customer. The next step in this evolution is an omnichannel strategy, now being deployed by some retailers, which presents a consistent shopping experience across mobile, web, and in-store channels. Omnichannel also enables retailers to integrate back-end infrastructure technologies (e.g., servers, databases, etc.) and cloud-based services (e.g., loyalty programs, personalized recommendations, inventory management, etc.) to improve many aspects of store and enterprise operations. An omnichannel strategy relies on several core and supporting technologies. The key factors in evaluating any omnichannel-enabling solution includ
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Epson
Published By: IBM     Published Date: Oct 13, 2016
Compare IBM DB2 pureScale with any other offering being considered for implementing a clustered, scalable database configuration see how they deliver continuous availability and why they are important. Download now!
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data. queries, database operations, transactional databases, clustering, it management, storage
    
IBM
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: 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: VMTurbo     Published Date: Mar 25, 2015
An Intelligent Roadmap for Capacity Planning Many organizations apply overly simplistic principles to determine requirements for compute capacity in their virtualized data centers. These principles are based on a resource allocation model which takes the total amount of memory and CPU allocated to all virtual machines in a compute cluster, and assumes a defined level of over provisioning (e.g. 2:1, 4:1, 8:1, 12:1) in order to calculate the requirement for physical resources. Often managed in spreadsheets or simple databases, and augmented by simple alert-based monitoring tools, the resource allocation model does not account for actual resource consumption driven by each application workload running in the operational environment, and inherently corrodes the level of efficiency that can be driven from the underlying infrastructure.
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capacity planning, vmturbo, resource allocation model, cpu, cloud era, it management, knowledge management, enterprise applications
    
VMTurbo
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