Ponder helps you run your Python data workflows at scale directly in your data warehouse. Seamlessly move from prototype to production using the tools that data teams know and love.
Ponder brings the best of both worlds: a fully pandas-native experience that is familiar and fast to prototype, plus the scalability and reliability of operating in a data warehouse.
Iterate on your Pandas workflows quickly, from prototype to deployment, all running securely within your cloud-native data warehouse. Turbocharge your productivity and speed up development cycles with lightning-fast, interactive results.
Get StartedRun your Pandas workflows at all scales, from megabytes to terabytes, without changing a single line of code. No more painful out-of-memory errors or slow single-threaded execution.
Get Starteddf.merge()
df.pivot()
df.fillna()
df.describe()
df.explode()
df.merge()
df.pivot()
df.fillna()
df.describe()
df.explode()
Don’t let your warehouse investments go to waste. Leverage your existing data warehouse as compute. No additional infrastructure setup required.
Get StartedPonder was founded by the creators of the popular open-source library Modin, which enables data scientists to run pandas at scale on distributed computing backends, such as Ray or Dask. Modin is embraced by the community and has seen adoption across sectors, including by the world's leading AI companies.