I think there's an additional important difference and that's optimization and query cost. Warehouse-native apps owned by other teams run queries directly on the warehouse, owned the by the data team. With additional queries comes a price, absorbed by the data team. If this doesn't have oversight, it's easy to rack up a pretty hefty Snowflake bill. The optimization of query efficiency and cost is up to the vendor, but most warehouse-native tools are very early and aren't talking about it yet. It remains to be seen if there is an additional cost, and if so, if there's a savings that will make an organization come out net-positive.

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Jan 1Liked by Arpit Choudhury

Thanks for this post.

When we first moved from on-premise to SaaS, the analogy was it's like plugging your appliance into a socket vs running your own electricity generator at home. SaaS was compelling

Today, indeed, it does feel like each appliance is powered it's own fully integrated electric companies. And those electric companies are sharing data (ELT - RETL) to get 360 view of your house. Now that Warehouses are SaaS, it feels like warehouse native apps are compelling with a singular backend (also in the cloud)

Which are the top Warehouse native apps you're tracking?

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Jun 29, 2022Liked by Arpit Choudhury

I think users will never be satisfied with a R-ETL setup. Mainly two reasons

1. Because wherever there is data sync, there is a chance of data loss / discrepancy. E.g. Companies can sync data in their marketing tool even now without R-ETL using Segment. But still they can’t trust the data in their marketing tool because of data loss issues.

2. No one would like to work back and forth between two tools - reverse ETL for data sync and mapping, and their main tool for everything else.

The other advantages like unlimited data retention, data security, low setup time, etc are added benefits.

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