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.
With Snowflake's new OpenFlow offering based on Apache Nifi, Snowflake will be able to become Fivetran faster than Fivetran can become Snowflake/Databricks, though....
OpenFlow feels like an attempt at keeping customers within Snowflake boundaries, and while it might work for some, I see no way Snowflake being able to keep up with the data integration needs unless they allow another way of extending their capabilities other than pre-built integrations.
On the other hand, I do agree with you that it is quite a big challenge for Fivetran to try and become Snowflake.
How will Fivetran and dbt who are detested for being overpriced and underfeatured in the segment they are supposed to be good at (ETL/ELT) be taking on being a datalake? That's orders of magnitude more complex in engineering and operating and they have no experience. This is really a play to consolidate, get rid of duplicate functions and provide a better experience to customers.
This seems to undermine the engineering muscle these companies have. Fivetran is well-capable of building a query engine, and with this merger, they also get access to SDF's query engine. They have the engineering capabilities, as well as the capital to attract the talent where needed.
I would not underestimate any of these players in the space.
Not that surprising. How many millions has been piled into dbt Labs?
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.
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/).
Fivetran acquired Census (reverse-etl) & Tobiko (dbt alternative).
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.
Observability is a good guess, but I'd venture to guess that the conversations going on internally are about how to capture value across the entire stack. I wouldn't be surprised if we hear about them acquiring either a database/warehouse company and/or an analytics solution. Or vice versa, them getting acquired by a bigger player that wants to offer more connectors and data modeling functionality.
That was the first thought I had, too. When the dot-com bubble burst, every VC was slapping companies together to try to forestall the black mark of having a “failure” and balance sheet write off that they would have to show the LPs (investors) in the next LP meeting. It got so bad that someone described it as “tying together two rocks and seeing if they will float.” Needless to say, most didn’t. So, this makes me wonder if we’re seeing the first signs of the bursting of the AI bubble which we all know we’re in the middle of. Maybe it’s legit and there is real “synergy” or whatever, but the fact that this is two companies within the same VC portfolio makes it suspect.
That happened at a company I was at 8 years ago. It acquired a company also owned by the major investor. Layoffs started with a month. They whole thing shut down within 6 months.
Maybe, but now they could IPO confidentially as a tech company with high revenue with a multi-billion dollar valuation, which sort of sounds like their end goal
those are heavy accusations to toss around and that the title would like you to conclude, but doesnt pass the basic smell check of fivetran's founders still having control of the company. dbt was the hottest company in the data world 3 years ago and is valuable.
Interesting. It makes sense with Fivetran and dbt being so complimentary, ingestion (Fivetran) vs transformation (DBT).
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?
Thoughts on possible implications for users in foreseeable future? We built a lot using dbt and can't really think of going back or switching to alternatives
Fivetran isn't really much of a transformation layer so this is likely just a move to lock-in customers of both companies by upselling an ingestion/transformation layer to existing customers.
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...
Full disclosure: I am a PM at Fivetran who is very excited about this.
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.
I'm wondering too. We run dbt on-prem. Worst that could happen is we don't get any more free updates. But we have the software and it will continue to run.
What's the problem specifically? Are you banking on some future features? Can't fix the bugs yourself? Worried it won't be compatible with future data warehouses?
I know people don't like it these days, but you can just continue to run old software.
> Data startups Fivetran and dbt Labs will merge in an all-stock deal, creating a combined data infrastructure company with nearly $600 million in annual revenue, the two companies told Reuters.
They specifically mention the dbt-core will remain open source and will be supported. However this type of consolidation will very likely bring increased prices.
I hope Fivetran alternatives like dlt remain open source.
Disclaimer: I am the co-founder of a dbt alternative, Bruin. (https://github.com/bruin-data/bruin)
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.
With Snowflake's new OpenFlow offering based on Apache Nifi, Snowflake will be able to become Fivetran faster than Fivetran can become Snowflake/Databricks, though....
Thoughts?
OpenFlow feels like an attempt at keeping customers within Snowflake boundaries, and while it might work for some, I see no way Snowflake being able to keep up with the data integration needs unless they allow another way of extending their capabilities other than pre-built integrations.
On the other hand, I do agree with you that it is quite a big challenge for Fivetran to try and become Snowflake.
How will Fivetran and dbt who are detested for being overpriced and underfeatured in the segment they are supposed to be good at (ETL/ELT) be taking on being a datalake? That's orders of magnitude more complex in engineering and operating and they have no experience. This is really a play to consolidate, get rid of duplicate functions and provide a better experience to customers.
This seems to undermine the engineering muscle these companies have. Fivetran is well-capable of building a query engine, and with this merger, they also get access to SDF's query engine. They have the engineering capabilities, as well as the capital to attract the talent where needed.
I would not underestimate any of these players in the space.
They also acquired Census recently - reverse ETL.
Not that surprising. How many millions has been piled into dbt Labs?
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.
It's the right move if they want to IPO.
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/).
Fivetran acquired Census (reverse-etl) & Tobiko (dbt alternative).
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.
Observability is a good guess, but I'd venture to guess that the conversations going on internally are about how to capture value across the entire stack. I wouldn't be surprised if we hear about them acquiring either a database/warehouse company and/or an analytics solution. Or vice versa, them getting acquired by a bigger player that wants to offer more connectors and data modeling functionality.
This smells like self-dealing on the part of A16z.
How so? It sounds like a pretty normal merger to me.
That was the first thought I had, too. When the dot-com bubble burst, every VC was slapping companies together to try to forestall the black mark of having a “failure” and balance sheet write off that they would have to show the LPs (investors) in the next LP meeting. It got so bad that someone described it as “tying together two rocks and seeing if they will float.” Needless to say, most didn’t. So, this makes me wonder if we’re seeing the first signs of the bursting of the AI bubble which we all know we’re in the middle of. Maybe it’s legit and there is real “synergy” or whatever, but the fact that this is two companies within the same VC portfolio makes it suspect.
That happened at a company I was at 8 years ago. It acquired a company also owned by the major investor. Layoffs started with a month. They whole thing shut down within 6 months.
is this why Reddit and Infogami merged?
I don’t know
Maybe, but now they could IPO confidentially as a tech company with high revenue with a multi-billion dollar valuation, which sort of sounds like their end goal
VCs often help companies find homes within their portfolios
those are heavy accusations to toss around and that the title would like you to conclude, but doesnt pass the basic smell check of fivetran's founders still having control of the company. dbt was the hottest company in the data world 3 years ago and is valuable.
You're so close to the subject of the accusation by association, that your commentary actually makes their accusation stronger.
Interesting. It makes sense with Fivetran and dbt being so complimentary, ingestion (Fivetran) vs transformation (DBT).
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?
There's the slim ci best practice and ways to deploying only what's changed in dbt, but these require some config and underlying knowledge.
Verifying schema changes pre-production is only part of the issues, figuring out the actual data changes caused by code logic changes is trickier.
Last month Fivetran also acquired Tobiko, maker of SQLMesh, a dbt alternative. Looks like they are going all in. https://www.fivetran.com/press/fivetran-acquires-tobiko-data...
And paying to eliminate competition along with way...
Thoughts on possible implications for users in foreseeable future? We built a lot using dbt and can't really think of going back or switching to alternatives
Fivetran isn't really much of a transformation layer so this is likely just a move to lock-in customers of both companies by upselling an ingestion/transformation layer to existing customers.
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...
Full disclosure: I am a PM at Fivetran who is very excited about this.
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...
Are you using their cloud offering or just the software itself?
Just the software
What's the lock-in?
The cloud component is probably sticky if you have come to rely on those parts.
I'm wondering too. We run dbt on-prem. Worst that could happen is we don't get any more free updates. But we have the software and it will continue to run.
the concern is that dbt-core will become stagnant.
It basically already has since they started developing dbt Fusion, so in that respect this probably doesn’t change much.
I expect they’ll keep developing Fusion but possibly as even more of a commercial-only offering than it already was.
What's the problem specifically? Are you banking on some future features? Can't fix the bugs yourself? Worried it won't be compatible with future data warehouses?
I know people don't like it these days, but you can just continue to run old software.
dbt in particular is effectively useless without maintained and up-to-date connectors to your particular database.
> Data startups Fivetran and dbt Labs will merge in an all-stock deal, creating a combined data infrastructure company with nearly $600 million in annual revenue, the two companies told Reuters.
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.
They specifically mention the dbt-core will remain open source and will be supported. However this type of consolidation will very likely bring increased prices.
I hope Fivetran alternatives like dlt remain open source.