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

	NBi http://www.nbi.io/	Nose https://nose.readthedocs.io/en/latest/
Programming language	.NET	Python
Category	Integration Testing, Unit Testing, Acceptance Testing	Unit Testing, unittest Extensions
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	Nose is a Python unit test framework This is a Python unit test framework that intergrates well with doctests, unnittests, and 'no-boilerplate tests', that is tests written from scratch without a specific boilerplate.
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 nose is a unit testing tool which is very similar to unittest. It is basically unittest with extensions therefore just like unittest is can test front-end components and behaviour
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 Nose can test back-end components and functionality as small units. One can write tests for each function that provides back-end functionality
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	No	Yes nose supports fixtures at the package, module, class, and test case levels, so that initialization which can be expensive is done as infrequently as possible.
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	Yes Group fixtures are allowed with nose, where a multitest state can be defined.
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	Through use of third party libraries like test-generator and from the 'unittest.TestCase' library
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	GNU Library or Lesser General Public License (LGPL) (GNU LGPL)
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 The nose library extends the built-in Python unittest module therefore has access to unittest.mock
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	Yes With nose it collects tests automatically and there’s no need to manually collect test cases into test suites.
Other Other useful information about the testing framework