PostgreSQL vs. SAS Enterprise Guide

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.

Incentivized

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.

Incentivized

• 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.

Incentivized

• 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.

• 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.

Incentivized

• 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.

As a needed software for day to day development activities

Incentivized

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

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.

Incentivized

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.

Incentivized

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

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

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.

Incentivized

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

Incentivized

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.

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.

Incentivized

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.

Incentivized

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

Incentivized

• 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.

Incentivized