Audience
Any business and organization seeking a solution to manage their cloud operations
About SQL Server
Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.
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SQL Server
SQL Server Reviews
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Probability You Would Recommend?1 2 3 4 5 6 7 8 9 10
"Microsoft SQL server offers excellent alternatives in SQL management" Posted 2021-03-18
Pros: SQL server offers enough security to be able to perform reliable transactions, where you can work with all kinds of procedures previously saved for SQL. In terms of relational databases, SQL server allows the inclusion of relational data licenses within multidimensional groups, which at the level of analysis makes things much easier. Recommended because you can work with up to 6 different types of licenses, so the number of clients that can be added to the platform is huge depending on the size of the company. For example, the Enterprise plan is usually around 25,000, but offers a very large number of servers to work with.
Cons: When working with pages simultaneously, there is a limit on the number of connections that can be carried out, and it has many restrictions that end up affecting the page editing level. For example, the size of the pages is impossible to edit, which leads to a somewhat poor view of the page in terms of size (it looks very small), as well as remaining static.
Overall: Something that elevates SQL server much more in contrast to other software of its kind, such as Oracle, is that you can add DDL and DML commands inside the graphs, which previously was not possible. As for servers, SQL server allows the administration of external servers when it is necessary to resort to its data lists, and if it is configured in client-server mode it is possible to administer the information so that it can be accessed depending on whether or not it is a client within the work network.
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Probability You Would Recommend?1 2 3 4 5 6 7 8 9 10
"Microsoft SQL server leads to a better prepared data management standard" Posted 2021-03-17
Pros: The interoperability that Microsoft SQL server brings serves to create a complete network in which databases are properly secured and at the same time can be edited by specific employees. Microsoft SQL server provides the user with the possibility of transporting large amounts of data of different types through the cloud. Our professional recommendation is that, if you choose to work with Microsoft SQL server, you should purchase the standard version, since it has all the features of software such as MySQL and Sybase ASE in terms of support for procedures and work in server mode, which would be enough to obtain promising results.
Cons: The Microsoft SQL server platform does not support the ability to manage Canvas scripts directly from the development data lists being used (specifically HTML) so adding Canvas code to that language is useless if the content is to be transported through Microsoft SQL server. The variety of DDL commands that Microsoft SQL server allows to implement is a bit small, which ends up limiting the work to only using DML commands.
Overall: Microsoft SQL server is the best option for working with large data servers, demonstrating that it is unnecessary to pay for large-scale enterprise plans in order to have large-scale results. It is very interesting to be able to count on its support for large engine data, but to base it on a smaller scale management, since the results are fast and the information can be transported to different destinations simultaneously without problems occurring.
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