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* '''Fast filtering''' - Sub-second filtering over the contents of the whole datastore, independent of size, saves the application developer from declaring and managing indexes that do the same: There is sufficient information in the queries to determine which indexes should be built to deliver a quick response.
* '''Fast aggregates''' - Sub-second calculation of statistics over the whole datastore saves the application developer from building and managing caches of those aggregates.
* '''API is a query language (SQL?, MDX?)''' - Building upon the formalisms, and familiarity, of existing query languages, we reduce the learning curve, and also provide Active Data implementations with more insight into the intent of the client application; and optimize for its use cases.* '''Uniform, Cartesian space of values''' - Mozilla has a mandate of data driven decision making. Data analysis tools, like Spreadsheets, R, Scipy, Numpy, and Pandas are used to perform data analysis, and they all require uniform data in multi-dimensional arrays, commonly known as "pivot tables" or "data frames". ActiveData's objective is to provide query results in these formats
* '''Metadata on dimensions and measures''' - ActiveData also provides context to the data it holds. It serves the purpose to allow exploration and discovery by third parties; by describing unit-of-measure, how dimensions relate to others, and provide human descriptions of the columns stored. This metadata is also invaluable in automating the orientation and formatting of dashboard charts: Knowing the domain of an axis allows code to decide the best (default) chart form, and provides logically reasonable aggregate options.
* '''Has a security model''' - Simpler applications can avoid the complications of a security model if it is baked into the ActiveData solution. If ActiveData is to become mainstream it is important that it can manage sensitive data and PII.
