Google Cloud SQL vs. PostgreSQL vs. Microsoft SQL Server

Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.

Incentivized

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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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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• It has a easily and user understandable interface which provides it every necessary feature to come up with.
• It's backend is very strong that can help us to run big quieres without any hesitation.
• It's integration with other tools are one of the powerful feature which makes it more suitable to use.

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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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• 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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• Increasing support for more database engines may enable a wider range of application needs to be met.
• Implementing and updating cutting-edge security features on a constant basis.
• Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.

• 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

• 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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It fits the current needs and bandwith of out lean organization.

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As a needed software for day to day development activities

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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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As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.

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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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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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GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.

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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.

Incentivized

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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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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Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.

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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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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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• Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
• Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
• It was cheaper than the legacy aws service since we needed large database instances

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.

• 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.

Incentivized