EDB Postgres Advanced Server vs. Google Cloud SQL vs. PostgreSQL

It's great if you are using or wish to use PostgreSQL and need the added performance optimization, security features and developer and DBA tools. If you need compatibility with Oracle it's a must-have. There are many developer features that greatly assist dev teams in integrating and implementing complex middleware. It's great for optimizing complex database queries as well as for scaling. I would recommend Postgres Plus Advanced Server for any software development team that is hitting the limit of what PostgreSQL is capable of and wants to improve performance, security, and gain extra developer tools.

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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.

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PostgreSQL is best used for structured data, and best when following relational database design principles. I would not use PostgreSQL for large unstructured data such as video, images, sound files, xml documents, web-pages, especially if these files have their own highly variable, internal structure.

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• PPAS Oracle compatibility, especially the PL/SQL syntax, has made migrating database-tier code very simple. Most Oracle packages do not need to be changed at all and those that do are generally for simple reasons like a reserved word in PPAS that is allowed in Oracle.
• PPAS xDB, the multi-master replication tool, is simple and - most important - does not break with network or other interruptions. We have been able to configure and forget, which our customers could never do with other multi-master tools.
• Most people had no idea that PPAS and PostgreSQL have full CRUD support for JSON. They think you need a specialized product and/or that JSON is read-only. Every organization that I have worked with is evaluating adding JSON to their relational model.

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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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• It works well with external data sources and runs on platforms with stable performance.
• Clients can rest assured that their personal information will be safe and secure.
• Many forums discuss setup and usage, and most are free.
• Adding tooling applications to a computer is unlimited.
• PostgreSQL runs on many OS platforms and supports ANSI SQL, stored procedures, and triggers.

• Documentation is excellent but spread out across many resources and can take a while to wade through—would benefit from having more intro level, getting started guides for various languages.
• Ruby support is excellent but more Ruby examples and beginner-level documentation would be nice.
• It is sometimes hard to find a community of users on StackOverflow so a larger community, and a dedicated forum with active members to answer questions and work through issues would be nice.

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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.

• Clearer indications on what is the query plan, to optimize the query
• More out of the box, Postgres specific, SQL functions
• It would be nice to have a more visual aid of the relationship between all tables, but possibly this depend more on the UI used

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

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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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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.

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

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PPAS proved better for our customer's data-centric apps than Oracle in all but a few edge cases (encryption at rest and multi-TB database-tier backups) because it is simpler to install/maintain, runs nearly all Oracle-syntax SQL as well as ANSI SQL. PPAS has much more JSON capabilities (full CRUD vs. read-only in Oracle), simpler geospatial, simpler / more stable replication and datatypes that match developer expectations, such as BOOLEAN and ENUMs.

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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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Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same family of applications that performs the company that develops it and that is not all bad, but being able to adapt or configure different programs, applications or other environments developed by third parties apart is what gives PostgreSQL a certain advantage and this diversification in the components that can be joined with it, is the reason why it is a great option to choose.

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

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• Postgres Plus Advanced Server is quite complex and may take longer to implement certain things than simply using PostgreSQL depending on developer familiarity with the platform.
• Getting up to speed can be daunting so again, there is an upfront cost in time spent learning the platform, besides the potential for extra time spent on a feature-by-feature basis.
• The cost of Postgres Plus Advanced Server should be weighed against simply using PostgreSQL to decide which is the best solution for your business needs.

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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

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• Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
• Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.
• It's free. You can't beat that.

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