top of page

A database for Pandas dataframes

Store all your df in one line

All logics covered: incremental concatenates, update dataframes or specific rows, all in one line of code

Cloud infrastructure

Deploy PandasDB in your AWS Cloud in no-time or use PandasDB Cloud and start using it in few clicks.

They believe in Pandas, they use our DB

Focus on data, forget the storage

Data teams are constraint because they need a flexible storage system, PandasDB solves it

All data teams using pandas got issues aligning with BackEnd teams and working in solutions so that they can focus in data not in accessing it

Screenshot from 2024-11-13 06-46-52.png

Creating ETLs, ML, AI Agents or Data Apps with Streamlit?

Python developers use PandasDB for different cases

Create Feature Stores easily

With PandasDB you can create your Feature Store without backend support or struggling with schemaless datalakes

Keep Streamlit always updated

Keep your Streamlit Data Apps always updated with the most powerful DB to store dataframes

Train & Test for Machine Learning

Machine Learning requires several tries and train datasets, later the test dataframes and the predictions need a room to be

Log your ETL input / output

Every time you transform data, it is good idea to save a backlog of the input / output. PowerDB allows you to store dataframes without limit

Industries

Trading

Trading applications use a zoo of dataframes from multiple sources. Keep track of all your data without effort

Software

Data teams in software companies struggle with IT teams to store and exploit their data. I/O freedom

Retail & eCommerce

Analytics and data applications are key for retail personalization, but data teams are constraint by IO

bottom of page