pre built database

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Published By: Group M_IBM Q3'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Group M_IBM Q3'19     Published Date: Sep 04, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q3'19
Published By: Oracle Global Marketing     Published Date: Jul 13, 2012
Read the Study that Adds Up to a 2,000 Hour Time Savings Versus SQL Server. ORC International, a global leader in market research, conducted a comparison study between Oracle Database Appliance and Microsoft SQL Server measuring productivity differences between the two solutions.
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database solutions, database appliance, pre-built database, pre-tuned clustered database, ready-to-use clustered database, disaster recovery, high availability, database rolling upgrades
    
Oracle Global Marketing
Published By: Microsoft     Published Date: Jul 20, 2018
When it comes to performance, Azure SQL Database is built for you, the developer. Azure SQL Database is designed to make your work easier and let you focus on other priorities. It scales on the fly, without downtime, with capabilities that make it great for building multitenant software as a service (SaaS) apps. Plus, it learns and adapts to your database workload, whatever that may be, using built-in intelligence to continually adjust and improve over time. That said, thereís more to a successful app than impressive performance. Thatís why we built Azure SQL Database to be just as intelligent in other areas, such as availability and security, so that you wonít need to worry about those essentials either. Finally, we built Azure SQL Database to let you work the way you want, using the tools and platforms you prefer. Itís why we call Azure SQL Database the intelligent database for developers. Read on to learn more, and weíre sure youíll agree.
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Microsoft
Published By: Group M_IBM Q2'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q2'19
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