dbForge Studio (Edge) vs. Enthought Canopy

This tool is useful for small and large IT departments and associated data analysts that perform direct database functions such as DBA tasks or extracting/importing data. Non-technical staff members would not benefit from this tool as much as the functions are detailed and technical. However, automation engineers will find this tool very open for automation, and can generate the scripting code for any of its functions.

Incentivized

Enthought Canopy is best suites for scripting data analytical concepts. It has a wide range of data analytical libraries and also is good for data visualization. I would not recommend using Enthought Canopy only as an IDE, there may be better options available. If you're looking for a good data simulation & visualization package, Canopy it is.

Incentivized

• Connection manager (we use it through ssh tunnels) works effortlessly.
• Great sync tools for both database schemas and data.
• Storing code snippets to be used when needed.
• Nice code suggestions while typing queries.
• Usually does very well with storing your session and opening all of your sql tabs when opening the apps next time.
• Does very well when executing large sql files (without opening the files into the application that is).
• Pretty good debugging help when a problem occurs in executing a query or a files with multiple queries.

Incentivized

• Providing scientific libraries, both open source and Enthought's own libraries which are excellent.
• Training. They provide several courses in python for general use and for data analysis.
• Debugging tools. Several IDEs provides tools for debugging, but I think they are insufficient or too general. Canopy has a special debugging tool, specially design for python.

• The ability to parameterize searches more would be advantageous. For example, being able to specify to only look for certain columns, certain data type changes, etc.
• The output reports from dbForge are very plain and could contain more detail, and perhaps be structured more like a pivot table form Excel

Incentivized

• Canopy does not support Python 3
• There were times the Python shell crashed, and I would have to restart it
• Some Python libraries are slow.

Incentivized

Although experience here is limited, as only one question has been asked and answered promptly, the registration and licensing process was very smooth and professional. There are forums online that discuss dbForge issues, as well as a Facts and Questions section on dbForge's website, so product support does seem to exist if needed.

Incentivized

Before choosing dbForge Studio I evaluated at least a dozen tools, especially on the Visual Query Builder function. For now, I have identified only one product that has a better Visual Query Builder than dbForge Studio. This other product also manages UNIONs, while dbStudio still doesn't do it visually. However, the better alternative product is enormously slower in operations and less feature-rich than DbForge Studio

Before Canopy with its python we were working with Matlab. We decided for Canopy against Matlab for two reasons: First, we believe that python together with NumPy or SciPy can achieve the objectives with less code and therefore less training, and second the prizes are much lower than matlab which is most robust, expensive and less intuitive. It's clear we are making the comparison with python and it has nothing to with canopy. But with Canopy you feel you have all those tools close together without the problem of configuration, besides a lot of personalized libraries that complements a typical python environment.

• Saved a TON of time when looking at massive amounts of parent/child data by allowing us to just use the master-detail browser.
• Very little training time needed for employees that are already used to using SQL Management Studio. This is a proper Windows UI application.
• Very cost effective to purchase the standard edition for every employee that needs it, but the free edition does most of what they need too!

Incentivized

• Its easier to define KPI's with Enthought
• It is good for reiteration and building on top of existing scripts
• Its dedicated Python console makes it easier to execute projects.

Incentivized