Hey Product Hunters! 👋
I’m Kalan — one of the founders of Pontoon, where we’re making it dead simple to send data exactly where your customers need it.
Pontoon was born out of a shared frustration we’ve felt in the data world:
→ As data engineers, we’ve spent too many hours wrangling brittle APIs and writing custom connectors just to get data out of SaaS tools.
→ As SaaS builders, we’ve seen how expensive and time-consuming it is to build and support clean, reliable APIs and integrations for customers.
We knew there had to be a better way, so we built Pontoon!
✅ With Pontoon, you can be up and running in under an hour, sending analysis-ready data products to your customers' destinations (Snowflake, BigQuery, S3, etc.) with just a few clicks.
✅ You connect Pontoon to your data store, map your models, plug in destination credentials — and you’re done. No custom APIs, no brittle pipelines, no code (unless you want it!)
✅ Pontoon is completely white label – whether you use our branded self-service flows or our SDK for a fully embedded integration, it’s up to you!
We built Pontoon with a ton of care because we deeply respect the responsibility of handling customer data. It’s a serious responsibility, and one Alex and I have been trusted with at some great companies.
If this is something you’ve been waiting for, we’d love for you to try it out. Feedback, questions, wild ideas — let us know, we're listening!
Thanks for checking us out!
Kalan
@pranay12 I was thinking about names related to lakes (because of data lakes) and the name Pontoon stuck (named after Pontoon boats).
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No-code data workflows are a big win for developers! 😄
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Congratulations on the launch of Pontoon! Simplifying data sharing is a significant step forward. How do you ensure data security and integrity during the transformation and delivery process without relying on traditional API methods?
@ica_lestari Thanks! We connect directly to the source and destination. This also helps with performance, as we can transfer millions of rows in minutes. For data integrity, we have multiple integrity checks, including row counts and checksums to verify that all rows were transferred properly.
Pontoon
Pontoon
Hi everyone, thanks for your feedback and support! Here's a quick FAQ based on questions we're hearing:
→ How does Pontoon ensure data security without traditional APIs?
✅ We connect directly to data stores using secure mechanisms like IAM
✅ We support strict access controls enabled by modern data platforms
✅ Our data transfer infrastructure is completely isolated and ephemeral
→ How are sensitive data elements handled during transfer?
✅ You are fully in control of which data elements Pontoon has access to
✅ You can filter or mask columns that are sensitive
✅ We don't store any data after a transfer is complete
→ How do we ensure accuracy and integrity of data?
✅ We run multiple integrity checks on every transfer, including row counts and checksums
✅ Always fail-safe: if there's an issue, we flag it and leave the destination in a consistent state
🚀 We're working on model versioning and schema evolution -- coming soon!
→ Can Pontoon handle larger data volumes?
✅ Yes! Unlike other integration platforms Pontoon is built for data replication
✅ We support incremental transfers, backfills and schedules ranging from near real-time to weekly batch
✅ We leverage optimized loading and unloading mechanisms depending on the data store
Thanks for the questions, keep them coming!
Congratulations on the launch! I am really curious about how the name Pontoon came to be
Pontoon
@pranay12 I was thinking about names related to lakes (because of data lakes) and the name Pontoon stuck (named after Pontoon boats).
No-code data workflows are a big win for developers! 😄
Congratulations on the launch of Pontoon! Simplifying data sharing is a significant step forward. How do you ensure data security and integrity during the transformation and delivery process without relying on traditional API methods?
Pontoon
@ica_lestari Thanks! We connect directly to the source and destination. This also helps with performance, as we can transfer millions of rows in minutes. For data integrity, we have multiple integrity checks, including row counts and checksums to verify that all rows were transferred properly.