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Thoughts on the new Claw migration partnership with Databricks? Looks vendor-locky.

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(@consultant_carl_42)
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Topic starter   [#12707]

Another week, another "strategic partnership" promising seamless, pain-free migration. Claw and Databricks are now offering a "co-engineered path" to move your data estate. I've read the press release and the technical brief, and I'm already getting flashbacks to the last time a vendor promised a "turnkey" solution.

Let's be clear: any migration path built and branded by a specific vendor, especially one as dominant as Databricks, isn't just a convenience. It's a calculated business move. They aren't building this out of altruism. The goal is to make it *just easy enough* to get you onto their platform, while making the thought of ever leaving seem prohibitively complex and expensive down the line. You're not buying a migration tool; you're signing up for a new set of architectural handcuffs, polished with a nice "partner" finish.

My skepticism isn't theoretical. In CRM migrations, we saw this with proprietary middleware that only worked one-way (into the new system). You'd get your data in, but the APIs for extraction were throttled or poorly documented, locking you into a specific ecosystem. I see the same patterns here:
* The pre-built connectors will undoubtedly favor Claw's specific data models and Databricks' Delta format, making assumptions about your schema that may not hold.
* The "optimized performance" will rely on proprietary features or configurations that don't translate to other platforms.
* The cost will be bundled in a way that seems cheap upfront but commits you to a specific consumption model on the other side.

Before anyone gets swept up in the hype, you need to ask the hard questions that this partnership is designed to make you gloss over:
* What is the actual, tested rate of data fidelity? Is it 100% for metadata, lineage, and permissions, or just the raw table structures?
* What is the ongoing operational cost *after* the migration, compared to your current baseline? Get it in writing.
* What is the exit path? If in 18 months you need to move a workload to Snowflake or BigQuery for cost or regulatory reasons, what does *that* migration look like?
* How much custom business logic in your current Claw workflows will need to be manually re-implemented, despite the "automation" claims?

This isn't about being anti-innovation. It's about recognizing a vendor land grab when you see one. A truly flexible architecture uses neutral, interoperable standards. This feels like the opposite. I'd recommend anyone considering this path to immediately commission a parallel proof-of-concept using a more agnostic toolset. The extra work now will save you from a painful, expensive divorce later.

-- Carl


Test the migration.


   
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