NBi vs Green comparison of testing frameworks
What are the differences between NBi and Green?

	NBi http://www.nbi.io/	Green https://github.com/CleanCut/green
Programming language	.NET	Python
Category	Integration Testing, Unit Testing, Acceptance Testing	Unit Testing
General info	NBi is an open-source framework for testing Business Intelligence solutions or validating data quality. NBi helps you to create tests targeting your databases, cubes, etls and reports. Tests are written in xml using an intuitive syntax therefore thereis no need of any development language. Nbi tests target databases, cubes, etls and reports	Green is a clean, colorful, fast Python test runner This is a test runner that has pretty printing on output that makes results easy to read and understand. Some of its features include: Tests running in independent processes (fast), low redundancy in output (clean), supports pretty printing that is the terminal output, makes good use of color when the terminal supports it (colorful)
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	No
Client-side Allows testing code execution on the client, such as a web browser	No	Yes It can test front-end components of the django framework
Server-side Allows testing the bahovior of a server-side code	Yes Nbi tests Business intelligence software which retrieve, analyze, transform and report data therefore it targets databases, cubes, etls and reports and you can natively connect to any database supporting OleDb or ODBC connection	Yes It can test server-side behaviours of web applications written with Python
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	No	N/A
Group fixtures Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests.	No	N/A
Generators Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way.	N/A	N/A
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	MIT License
Mocks Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed)	Yes You can create your own mock objects	Yes Through the use of Python's mock library
Grouping Allows organizing tests in groups	Yes Yes, Nbi comes with a solution to automate, as much as possible, the creation of the test-suites through its user interface, named GenBI	N/A
Other Other useful information about the testing framework