u/howMuchCheeseIs2Much

Sync attio + ads data into a datalake / data warehouse then sync the ad data back into Attio.

There are a few separate tools to do this (which some others have mentioned), but Definite (https://www.definite.app/) does this all in one product.

We use Attio ourselves as our internal CRM and about 30% of our customers use Attio.

Founder of Definite here, so take this with a grain of salt, but we built the product specifically for this frustration.

The core problem we kept seeing was teams stitching together connectors, warehouses, and BI tools, then building dashboards that nobody actually uses. People just end up asking the data person questions anyway.

So we built an AI analyst that sits on top of a unified data stack. You connect your sources, we handle the warehousing, and then anyone on the team can just ask questions in plain English instead of waiting on dashboard requests.

Happy to answer questions if anyone's curious. Not trying to pitch hard, but we loved Looker and built Definite to have something better live on after it went downhill.

Founder of Definite here, so take this with a grain of salt, but we built the product specifically for this frustration.

The core problem we kept seeing was teams stitching together connectors, warehouses, and BI tools, then building dashboards that nobody actually uses. People just end up asking the data person questions anyway.

So we built an AI analyst that sits on top of a unified data stack. You connect your sources, we handle the warehousing, and then anyone on the team can just ask questions in plain English instead of waiting on dashboard requests.

Happy to answer questions if anyone's curious. Not pitching hard, but I loved Looker and built Definite to live on after Looker went down hill.

Metabase is still great if you:

• already have good warehouse + transformation + ingest layers
• mostly need simple dashboards
• don’t care about pixel-perfect decks

The "modern data stack" is getting weird (Fivetran buying dbt, etc.) and will eventually consolidate to a single vendor solution, so having a stand alone BI probably isn't going to last long.

Where it feels dated in 2025 is that most people expect AI built-in: natural language querying, auto-generated charts, smart joins across sources, explanations, etc. Metabase has made some progress, but it’s still fundamentally a SQL-first BI tool.

If I were making this decision today I’d ask:

• Do we want a “viewer on top of a warehouse,” or do we want the whole stack (ingest + warehouse + BI + AI) in one place?
• How important is AI-assisted analysis vs just static dashboards?
• Who are the main users – analysts comfortable in SQL, or business users who never will be?

Full disclosure: I work on an AI-native analytics product in this space (Definite)

you're right! wrote quickly on mobile, fixed!

DuckDB is single node, so there are some fundamental limits there where if you have many PBs of data, DuckDB is not the right choice.

Tableau was acquired by salesforce and is < 10% of their total revenue. It's possibly even smaller than Slacks revenue now (also acquired by Salesforce), so I wouldn't bet on them for innovation. Products that are acquired like this do not have a great track record historically.

We use Definite (definite.app) to track MRR. They also have a blog post about how they calculate it from Stripe data that goes into the details—handling trials, cancellations, upgrades, etc. Pretty helpful if you're dealing with Stripe and want something accurate.

https://www.definite.app/blog/stripe-mrr-calculation

I read about how to calculate current MRR from Stripe data in this blog post: https://www.definite.app/blog/stripe-mrr-calculation. It explains how to handle things like trialing users, cancellations, and subscription changes. Might be helpful for what you're trying to do

to be clear, I'm recommending you stick with plain DuckDB:

at a smaller scale, without Ray / 3FS is likely slower than vanilla DuckDB and a good bit more complicated.

I mention Definite as it's one of the easiest way to use DuckDB at a company.

smallpond is easy to spin up (I even link to a version with S3), but it'd be very challenging to get 3FS spun up right now and you'd need 3FS to get the performance above.

it won't work with Snowflake, but we built a dbt alternative specifically for duckdb. It has table and column lineage using duckdb's built-in functions (e.g. json_serialize_sql).

https://github.com/definite-app/crabwalk

this is an open source project, not a hosted service