Dbt Labs acquires SDF Labs(getdbt.com) |
Dbt Labs acquires SDF Labs(getdbt.com) |
In December 2024 the page had been updated to now compare "dbt Core" against "SDF with dbt": https://web.archive.org/web/20241217172451/https://www.sdf.c...
Little marketing switcharoo there to avoid pissing off their future owners.
Alas, dbt Labs has developed a reputation for rug pulling functionality from dbt Core and gating most of their differentiating features behind dbt Cloud. I cannot see this type of consolidation being in the best interest of the dbt community.
Their CEO and founder spoke of an IPO in 2022.
Let's not pretend they are still remotely close to their humble beginnings or were able to get this far without credibly demonstrating they have a plan for how to make enterprises bleed through their nose for their product.
That's the future.
On the flipside, building a dbt adjacent product enhancing or complementing capabilities is basically a sure way of how to get bought.
For our (https://www.definite.app/) use case, I'd love to have something that compiles client-side, but in general dbt just feels like a lot of work to set up for what most of our customers actually need (simple transform to create tables and views).
I'm quite surprised to hear that.
It's literally pip install, a single file for your DB config and that's it. 30-40 seconds.
I'm in no way affiliated with dbt but have worked with the tool since 2018.
Lighter, faster, sure, but hard to set up?
I'm not sure where you'd want to cut corners on setup.
- The dbt docs functionality is no longer maintained in favor of dbt Explorer in dbt cloud. A natural consequence is that larger dbt Core projects simply cannot leverage local docs due to performance defects.
- Multi-project support was widely discussed in the core repo w/ tooling contributions from the community, but that was locked behind enterprise-tier dbt cloud accounts
- Metricflow was a full OSS application that used to work in tandem with dbt Core. Post-acquisition, the original code was re-licensed and the functionality added to Cloud only (and you have to pay per semantic layer query now).
Again shows we have run out of 3 letter acronyms :)
For context, the team behind SQLMesh also develops SQLGlot, which powers the features dbt attempts to implement
SQLGlot is a Abstract Symbol Tree SQL Dialect transpiler that could (in theory) convert from one dialect to another (bi-directional).
SQLMesh appears to combine both of the above into one tool that sounds like it's even better.
(Asking as I kinda wish my company’s opinionated dbt had made some different choices)
Frankly, the dbt product hasn't really evolved much. I've been a bit disappointed with its lack of evolution toward this stuff organically. The "modern data stack" is in kind of in a magic position where they are working at very technical companies but the people using it are not SWEs who can build out the tooling themselves so they are just getting buckets of money without a really big value proposition. My team self hosts a dbt core workflow and it's been almost trivial to build out dbt's paid product ourselves
It has evolved quite a bit behind the paywall - as has the paywall.
Most if not all of this stuff will land behind, not before said wall.
A comparison that's obvious to my team is the release cadence of Metabase, which we also self-host. The frequent rollout of new features in Metabase is great and gives me more confidence in the product. But I'm not in the position to decide whether to cough up the $ for the paid version so I suppose it's moot.
I haven't checked yet, but is SDF schema-dependent? For some reason, all sql comprehending/transforming tools I can find are either too trivial to be useful or require an exact schema to operate, both of which are too brittle to be useful when I try to use them in anger.
https://web.archive.org/web/20241217210804/https://www.sdf.c...
Professional
For development teams looking to scale fast.
$1,250/mo
Annually
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Up to 1,500 models
Unlimited Team Members
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Unlimited compile, test, & runs
dbtlabs also sells dbt cloud, which provides a runtime for your dbt projects.
Dockerfile, env var injection and you're done.