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Hopefully, we can be another managed solution for those on GCP.

And as for your second point, yep, Spark tuning is definitely annoying! BigQuery is a lot more than jusr the engine, and building a simple interface for a complicated, high-performance process is hard. That's a big reason why I made ParaQuery.



You may want to look into DataMechanics who is another YC startup who tried something similar. They were acqui-hired by NetApp.

If I remember they focused on SME space because in enterprise you will likely struggle against pre-allocated cloud spend budgets which lock companies into just using GCP services. I've worked at a dozen enterprise companies now and every one had this.


Enterprises can deploy on their own GCP, and we're planning on releasing on GCP Marketplace.

For a similar cost, what if their pipeline were 5x faster, and they don't have to dealing with managing the deployment themselves?

Thanks for telling me about DataMechanics


a) Enterprises have almost entirely moved away from self-hosting software. GCP Marketplace is fine but I would probably also look at a Kubernetes option as many companies have GKE clusters.

b) It won't be 5x faster though and I wrongly recommend you don't take a marketing attitude when selling this type of software. Because it will be mostly technical engineers and architects deciding on this and we aren't stupid. I have run GPU accelerated Spark clusters for years for enterprise companies and you will be able to accelerate the query part of the pipeline but that's like 20% of what a typical job does.


a) Since being fully-managed is one of my value props, that's probably better for us.

b) Of course I'm only accelerating the Spark/query part. Not sure what you mean. And in that case, I took a query which was 44 minutes on BigQuery and ran it with a "comparable" cluster on ParaQuery in 5.5 minutes. Perf is slightly variable, so maybe it's 40 minutes vs 6 minutes. In that case, ParaQuery would still be 6.5x faster, and >2x cheaper. That being said, it was just a benchmark ETL query with some random data (50b rows), and these things do vary between workloads.

So yeah, without knowing more about the use case you're talking about, hard to say. Even Nvidia has a hard time optimizing certain TPS-DS queries btw, so it's not like I can just 5x anything!




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