PostgreSQL vs. SAS Enterprise Guide vs. Microsoft SQL Server

Based on my experience, PostgreSQL is exactly what I imagine when thinking of a relational database: it is fast for querying and intuitive (if the underlying relations have been well written) and its writes are also efficient. Of course you need to know that a relational database is what you need, for example I would not recommend it if you have a lot of unstructured data that have no way to create a relation from and if you need to run heavy aggregations over your data, as it is not where PostgreSQL would shine.

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For writing out longer code creation for shaping data on complicated reports, the clean UI is helpful. If exploring data though, SAS Studio would be better suited given its easier interface for GUI graph building.

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Microsoft SQL Server is ideal for highly available SQL workloads by using SQL Server Always On availability groups. Microsoft SQL Server might not be appropriate for solutions which require a very low resource footprint, since it requires significant CPU cores and RAM memory as well as high IOPS, always depending on the usage scenario.

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• The stability it offers, its speed of response and its resource management is excellent even in complex database environments and with low-resource machines.
• The large amount of resources it has in addition to the many own and third-party tools that are compatible that make productivity greatly increase.
• The adaptability in various environments, whether distributed or not, [is a] complete set of configuration options which allows to greatly customize the work configuration according to the needs that are required.
• The excellent handling of referential and transactional integrity, its internal security scheme, the ease with which we can create backups are some of the strengths that can be mentioned.

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• It can load a huge amount of data as compared to R Studio and Excel.
• Data processing speed is very fast, millions of records are loaded into this software very easily and data manipulation is also very easy.
• Inbuilt Statistical functions and procedures make it very comfortable to use for non analytics professionals as well.

• Easy to configure and use with Visual Studio and Dot Net
• Easy integration with MSBI to perform data analysis
• Data Security
• Easy to understand and use
• Very easy to export database and tables in the form of SQL query or a script

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• The query syntax for JSON fields is unwieldy when you start getting into complex queries with many joins.
• I wish there was a distinction (a flag) you could set for automated scripts vs working in the psql CLI, which would provide an 'Are you sure you want to do X?' type prompt if your query is likely to affect more than a certain number of rows. Especially on updates/deletes. Setting the flag in the headless(scripted) flow would disable the prompt.
• Better documentation around JSON and Array aggregation, with more examples of how the data is transformed.

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• I would like to see advance interactions with external databases to be able to kill ongoing queries from SAS. As of now, you can stop pretty much any ongoing process besides the one running on a remote database (killing SAS/EG doesn't stop the remote process)
• When creating prompts for programs, it would be nice to be able to have conditional prompts (based on the selection of other prompts). The prompts are clearly a recent feature and constantly under development but I wish it would be more powerful.
• More of a SAS metadata issue but when loading SAS/EG (first connection to the server), it takes a few seconds which feels like a long time. I really don't understand why the initialization of the session can take so long. Don't get me wrong, this has no real impact on productivity but that 10s delay just feels really like eternity when you want to run some code in a new session.

• The import/export process can be tricky to follow with lots of steps and could be better for importing flat files
• Obtaining help from Microsoft is cumbersome and often other internet sources are better and quicker
• The documentation is not great and again it's generally better to obtain help elsewhere if needed

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As a needed software for day to day development activities

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On account of current user experience and the organization-wide acceptance.

I think it is unlikely that sql server has disappointed someone, it is likely that someone will come initially discouraged if the needs and problems that occur are very challenging, but definitely have a SQL oriented system means having a solid base to work and on which maintain the their data securely

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Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.

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It's not all bad, but I don't believe that an enterprise purchase of SAS is worth the expense considering the widely available set of tools in the data analytics space at the moment. In my company, it's a good tool because others use it. Otherwise, I wouldn't purchase a new set of it because it doesn't have some of the better analytical functions in it.

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SQL Server mostly 'just works' or generates error messages to help you sort out the trouble. You can usually count on the product to get the job done and keep an eye on your potential mistakes. Interaction with other Microsoft products makes operating as a Windows user pretty straight forward. Digging through the multitude of dialogs and wizards can be a pain, but the answer is usually there somewhere.

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PostgreSQL's availability is top notch. Apart from connection time-out for an idle user, the database is super reliable.

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Its does not have outages.

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The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.

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SSAS data cubes may some time slow down your Excel reports.

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There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.

But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.

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Although I use SAS support for information on functions, these are SAS related and haven't really come across anything that is specifically for SAS EG.

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We managed to handle most of our problems by looking into Microsoft's official documentation that has everything explained and almost every function has an example that illustrates in detail how a particular functionality works. Just like PowerShell has the ability to show you an example of how some cmdlet works, that is the case also here, and in my opinion, it is a very good practice and I like it.

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It was good

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The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.

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very hands on and detailed training

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The online documentation of the PostgreSQL product is elaborate and takes users step by step.

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I've not worked hands-on with the implementation team, but there were no escalations barring a few hiccups in the deployment due to change in requirement & adoption to our company's remote servers.

Other than SQL taking quite a bit of time to actually install there are no problems with installation. Even on hardware that has good performance SQL can still take close to an hour to install a typical server with management and reporting services.

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In my experience using all of these products over many years, PostgreSQL is better than any of them in reliability, performance, productivity, cost, scalability and interoperability across operating systems.

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Python-based platforms like Pandas or Spark are very good too at displaying data and do exploratory analysis. I definitely prefer them to SAS EG. It's just too slow, and doesn't let you peek into the data very easily. Lots of clicking, and I'd rather just write some code, rather do clicking.

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Microsoft SQL is slower than MySQL and Access but far more feature-rich and reliable. Access is almost obsolete nowadays, so not too many people are considering it, but unless budget or an open-source ethos is a factor, Microsoft SQL is superior in every way. Many commonly used tools, like Crystal Reports, support it.

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The DB is reliable, scalable, easy to use and resolves most DB needs

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SQL server does handle growing demands of a mid sized company.

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• A robust and reliable platform reduces the risk of data loss and confusion.
• Using an almost free product is economical. No license fees = minimal ownership cost.
• Efficiency is high due to quickness and excellent resource management.
• PostgreSQL helps us achieve our goals, and there are no time-consuming management tasks.

• Faster decision making, through powerful big data handling functionalities.
• Faster operations on daily basis, once the project tree is built, unskilled personnel can use it in their daily operation.
• Don’t need to choose SAS EG if you are not going to be handling big data. (such as over 1 million rows and 50 columns)
• You need skilled personnel to build the initial project tree.

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• Increased accuracy - We went from multiple users having different versions of an Excel spreadsheet to a single source of truth for our reporting.
• Increased Efficiency - We can now generate reports at any time from a single source rather than multiple users spending their time collating data and generating reports.
• Improved Security - Enterprise level security on a dedicated server rather than financial files on multiple laptop hard drives.

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