Snowflake x Ponder

We're proud to announce that Ponder will join Snowflake to supercharge data science and AI in the Snowflake Data Cloud.

Your Python data workflows,
now running on your data warehouse

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.

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Data science, now with scale, security, and governance built-in

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.

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Get insight faster with Ponder. Speeding up Pandas API, including groupby, mean, and hundreds of other functions!

Clean data at scale,
with zero effort

Run 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.

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df.merge()

df.pivot()

df.fillna()

df.describe()

df.explode()

df.merge()

df.pivot()

df.fillna()

df.describe()

df.explode()

# import pandas as pd

import modin.pandas as pd

Time

Run Pandas everywhere

Don’t let your warehouse investments go to waste. Leverage your existing data warehouse as compute. No additional infrastructure setup required.

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From the team that brought you popular open-source library Modin

Ponder 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.

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8M+

Downloads to date

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40+

Used by companies & Organizations

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100+

Open Source Contributors

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8k+

Github stars

Powering data teams at the Fortune 100 and more!