When comparing DbForge Studio for PostgreSQL vs Schemaball, the Slant community recommends DbForge Studio for PostgreSQL for most people. In the question“What are the best database design programs?” DbForge Studio for PostgreSQL is ranked 12th while Schemaball is ranked 15th. The most important reason people chose DbForge Studio for PostgreSQL is:
Prompting the names of existing materialized views, as well as context prompting of database objects
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Pros
Pro Advanced code completion features
Prompting the names of existing materialized views, as well as context prompting of database objects
Pro Query Profiler
Helpful diagrams of query execution, and also the list of operations that takes place on the server
Pro Data Editor
The data can be edited in the same way as with Google Sheets/MS Excel or in the card view mode.
Pro High execution speed
Downloading the main_ExceptionFrames.sql file of 100 Mb in size ~ 1 min
Pro SQL Code Formatter
Automatic formatting of SQL Code based on user-chosen code styles
Pro Data Export/Import
10+ file format support, including Google Sheets
Pro Master-Detail Browser
The 'design view' for setting up relations between tables, smart sorting, and filtering
Pro Code complition
Prompting keywords for functions etc.
Pro Cached update mode in Data Editor
Allows to control data editing within database objects
Pro Generate Script AS feature
Allows generating a script for the CREATE statements for specific database objects (views, materialized views, triggers, functions, procedures)
Pro Object Explorer
Provides a quick navigation through the object tree
Pro File format support
Dozen of file formats are supported, including Google sheets.
Pro Supports reading schemas from multiple sources
Schemaball can read schemas from multiple sources such as SQL schema dumps, flat files or live databases.
Pro Interesting twist on visual interface
Gives a quick way to grasp an overview on the past/present complexity of the database (or group of tables) undergoing inspection.
Cons
Con Data export
Data export does an individual insert per row of data, which is a little inefficient.
Con Visualizations may be hard to get used to
Since schemas are visualized by using stylized "schema balls" it may be hard getting used to them since they are so different from the other, more straightforward options.