I think consolidation in the space has been coming for quite some time now and this merger only confirms what us, along with many others, have been saying: the data tooling is in a miserable state and we had to glue together a bunch of different tools that don't work with each other.
At this point, I think it is quite obvious that Fivetran is going for Snowflake/Databricks's market share. They own the ingestion for many companies already, and they will offer a managed data lake product in order to compete with the data giants. By owning the means of bringing the data in (Fivetran) as well as the transformation layer (dbt/sqlmesh) they will aim to get ahead of Snowflakes of the world.
I think it'll be a win for the data community if they maintain and continue investing into the existing tooling, as they are running in quite a few places already, especially dbt core running in a self-managed way. I certainly hope they won't try to squeeze revenue for the sake of it from their combined users.
It's an interesting time to be in the space, and it feels great to be one of the few independent players in the market.
I would not underestimate any of these players in the space.
Thoughts?
Yes, OpenFlow may be able to replace the data movement part (though prefect, airflow, yadda yadda all tried to be the one ring), but it's a pretty small bunch who support all connections.
It's not the only part of the business, but it's an important one. Just like Plaid's approach became the standard to code against in accessing financial services, Fivetran has become the default in getting data out of tools you already pay for directly into a controlled space.
If they don't muck that up, they've got an embed in every large integration. No one is looking to OpenFlow for that.
Still won't become Snowflake or Databricks (and it's silly to try, imho), but they do have a good moat for a small castle.
On the other hand, I do agree with you that it is quite a big challenge for Fivetran to try and become Snowflake.
dbt Cloud is an uncompelling product. Fivetran is convenient but absurdly expensive. Now dbt core development is just another marketing cost for Fivetran.
I'd really love to see everyone move on from the "modern data stack". dbt is a sticking plaster to a problem caused by orgs aggressively adopting SaaS products and choosing distributed software architectures without any thought about how to deal with the problem that your data models don't fit together and data is stored in 30 different places.
They were part of the reason I started https://canine.sh as a way to self host more things. Had we had the confidence to host Airbyte or kafka + debezium as an option, we wouldn't have to deal with the atrocious pricing.
Everytime I bring up self hosting, the response is always a rote response of: "Its way too hard", "What if it goes down?", "Just delegate it to the professionals". To me this just seems incredibly defeatist, and its the same set of rebukes regardless if the cloud version costs $100 or $100,000.
end of rant.
I wonder who's next to really consolidate their platform play and compete with the old legacy MDM provider like Informatica. Data Observability or Catalog like Monte Carlo and Atlan. The whole Modern Data Stack has either died, acquired or merged by now. Wonder what's missing for Fivetran to IPO too.
I also wonder what this merge means for Airbyte who raised 150m at 1.5b in 2023.
The "modern data stack" market excluding of data warehouse / data lake is pretty small. Fivetran is biggest one and still under $500M in revenue, so they're acquiring other parts and starting to offer their own datalake (managed Iceberg).
Snowflake started offering fivetran-like connectors a couple years ago and I expect they'll double down there. Same with Databricks. Microsoft has Fabric now, but the reviews have been terrible (my experience included).
I think they'll each ultimately have a full data stack.
If you don't want to wait, we built a modern-data-stack-in-a-box at Definite (https://www.definite.app/).
last update we had was Fivetran had 200m in 2023 and 300m in 2024 (https://www.fivetran.com/press/fivetran-surpasses-300m-arr-d...)
if Fivetran continued at same pace in 2025, that means it's at 400m ish and dbt was at 200m. not bad for dbt.
The bigger question mark to me is that Fivetran recently acquired Tobiko, the company behind a dbt competitor SQLMesh. The Tobiko team said their focus has been on dbt-compatibility because a lot of Fivetran customers use dbt for their transformation layer. I fear it may have just been a way to get rid of competition leading up to this deal. I can't imagine Fivetran spent a ton of money just to have 2 products that do very similar things.
We use both open-source SQLMesh as well as their cloud offering Tobiko Cloud. Following the acquisition, we were annoyed that focus was going to go to dbt compatibility because there was a bunch of stuff on their roadmap that would help us that was now deprioritized. Thankfully, they still offer great support to us and delivered a few features that have given us some quality of life improvements. With this announcement, I'm worried we're going to end up being forced to migrate to dbt...
We are fully committed to open source dbt and don't want to build a 'walled garden'. Interoperability is one of the key value propositions of both Fivetran and dbt. While I'm biased, I think the main implications for users is that their favorite tooling will be with one vendor who cares about what makes them great.
You can read a bit more here: https://www.fivetran.com/blog/the-era-of-open-data-infrastru...
But I still feel like I'm missing, in DBT, capabilities for DB DDL/DML deployment (which I've done from Liquibase in DBT) for a fully CICD modern data stack. Preconditions, post-conditions, only-deploy-changed-code capabilities... Am I missing something in DBT?
Verifying schema changes pre-production is only part of the issues, figuring out the actual data changes caused by code logic changes is trickier.
I hope Fivetran alternatives like dlt remain open source.
