Pandasql vs Pome: What are the differences?
Developers describe Pandasql as "Make python speak SQL". pandasql allows you to query pandas DataFrames using SQL syntax. It works similarly to sqldf in R. pandasql seeks to provide a more familiar way of manipulating and cleaning data for people new to Python or pandas. On the other hand, Pome is detailed as "Postgres monitoring dashboard". Pome stands for Postgres Metrics. Pome is a PostgreSQL Metrics Dashboard to keep track of the health of your database. This project is at a very early stage and there are a lot of missing features, but I'm hoping to be able to make the project progress quickly.
Pandasql and Pome belong to "Database Tools" category of the tech stack.
Pandasql and Pome are both open source tools. Pome with 1.07K GitHub stars and 41 forks on GitHub appears to be more popular than Pandasql with 737 GitHub stars and 109 GitHub forks.