NanoCube is a minimalistic in-memory, in-process OLAP engine for lightning fast point queries on Pandas DataFrames. As of now, just 27 lines of code a

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2024-10-06 21:00:04

NanoCube is a minimalistic in-memory, in-process OLAP engine for lightning fast point queries on Pandas DataFrames. As of now, just 27 lines of code are required to transform a Pandas DataFrame into a multi-dimensional OLAP cube. NanoCube shines when point queries need to be executed on a DataFrame, e.g. for financial data analysis, business intelligence or fast web services.

If you believe it would be valuable to extend NanoCube with additional OLAP features and improve its speed - yes, that’s possible - please let me know. You can reach out by opening an issue or contacting me on LinkedIn.

Tip: Only include those columns in the NanoCube setup, that you actually want to query! The more columns you include, the more memory and time is needed for initialization.

Tip: Use dimensions with highest cardinality first. This yields much faster response time when more than 2 dimensions need to be filtered.