PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
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Sequel Pro
Score 9.0 out of 10
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Sequel Pro is a relational database software solution offered free and open source. It allows users to access any MySQL database through a Mac.
PostgreSQL is ideal for handling databases that contain large volumes of information due to its efficiency, speed and above all because of the good management it makes of our resources, it also behaves very well in distributed environments of high demand, if you want a database of stable data and excellent performance PostgreSQL is one of the best.
The performance of PostgreSQL has been enhanced through the years, but always is better to have as much performance as we can.
The replication services could be done directly within the database, and more easily.
The Object Orientation of the Database could be extended, and albeit it manages inheritance of tables, and accepts XML and JSON as primary types, it would be wonderful if one could attach methods more easily to tables (to make them more like classes), and instances (rows for example).
Improving the way we create new connections to remote databases
I couldn't find any way to configure my local server (MySQL), so I need to make changes on server outside the application. I know that there are other tools that integrate it, so you don’t have to leave the workflow
It could have a feature to integrate our databases or connections (favorites) with other devices, like using Google Drive or Dropbox. It would be really useful!
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.
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.
AWS, Heroku, and Digital Ocean all provide Postgres-as-a-service, where you pretty much never need to administrate it yourself but they do it for you. The Postgres community also has developed awesome and reasonably priced extensions, such as Citus DB and CockroachDB in case you need additional support for running it. If you need documentation, Postgres's docs are super thorough and their official forms are active.
It's open-source and very convenient to work with. I can easily import any database I want using a data dump and runt the queries on them to derive the data insights on the data. I might want to use Excel to visualize that, that might be one of the disadvantages.
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.
In this case, Postgres is preferred because it handles large data sets and requires fewer hardware resources than its competitor, MySQL. Compared to PostgreSQL, Microsoft products are excellent, but the installation process for MS SQL is lengthy. PostgreSQL has an advantage over its competitors in that it can adapt or configure third-party programs, applications, or settings.
MySQL workbench is good to work with MySQL databases, but Sequel Pro gives us the ability to work with any SQL databases. It's open-source, lightweight and solves the problem that I am required to solve to run the DDL and DML queries.
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.
Unreliability has lead to wasted time and frustration among staff.
The ease of testing database changes and modifying test data WHEN IT WORKS theoretically makes testing quick and easy but in reality, this is far outweighed by the wasted time and frustration involved with it not being reliable.
The ease of seeing the relations between tables is very nice and saves time when trying to see how unfamiliar tables are connected.
