I used to be a big fan of the platform because back in 2020 / 2021 it really was the only reasonable choice compared to AWS / Azure / Snowflake for building data platforms.
Today it suffers from feature creep and too many pivots & acquisitions. That they are insanely bad at naming features doesn't help either.
But these days just use trino or whatever. There are lots of new ways to work on data that are all bigger steps up - ergonomically, performance and price - over spark as spark was over hadoop.
The nice thing about spark is the scala/python/R APIs. That helps to avoid lots of the irritating things about SQL (the same transformation applied to multiple columns is a big one).
I really can't speak highly enough of Trino (though I used it as AWS Athena, and this was back when Trino was called Presto). It's impressive how well it took "ever growing pile of CSV/JSON/Excel/Parquet/whatever" and let you query it via SQL as-is without transforming it and putting it into some other system.
Hadoop was fundamentally a batch processing system for large data files that was never intended for the sort of online reporting and analytics workloads for which the DW concept addressed. No amount of Pig and Hive and HBase and subsequent tools layered on top of it could ever change that basic fact.
Databricks started in 2013 when Spark sucked (it still does) and they aimed to make it better / faster (which they do).
The product is still centered Spark, but most companies don't want or need Spark and a combination of Iceberg and DuckDB will work for 95% of companies. It's cheaper, just as fast or faster and way easier to reason about.
We're building a data platform around that premise at Definite[0]. It includes everything you need to get started with data (ETL, BI, datalake).
Aren't the alternatives you mentioned - icerberg and duckdb - both storage solutions while spark is a way to express distributed compute? I'm a bit out of touch with this space, is there a newer way to express distributed compute?
Flink is designed around streaming first, while Spark is built around batch first and you're likely best off selecting accordingly. Though any streaming application likely needs batch processing to some degree. Latency vs throughput.
DuckDB is not only a storage solution. It can directly query a variety of file formats at rest, without having to re-store anything. That's one of its selling points: you can query across archival/log data stored in S3 (or wherever) without needing to "ingest" anything or double-pay to duplicate the data you've already stored.
I’m just getting into DuckDB lately and finding this feature so exciting. It’s a totally new paradigm. Such a great tool for scientists, and probably many other people. I wish I took it seriously sooner.
duckdb is primarily a query engine. It does have a storage format, but one of it's strengths is querying data where it already resides (e.g. a parquet file sitting in S3).
There are some examples[0] of enabling DuckDB to manage distributed workloads, but these are pretty experimental.
I think what many people are finding out is they don’t really need distributed processing. DuckDB on a single node can get you really far, and it’s much simpler.
But if you're inclined to use it, databricks' setup of spark just saves you an incredible amount of time that you'd normally waste on configuration and wiring infrastructure (storage, compute, pipelines, unified access, VPNs etc). It's expensive and opinionated, but the data engineers you need to deal with spark OOM errors constantly is greater.
Also databricks' default configs give you MUCH better performance out of the box than anything DIY and you don't have to fiddle with partitions and super niche config options to get even medium workloads stable
Databricks is the Jira of dealing with data. No one wants to use it, it sucks, there are too many features to try to appease all possible users but none of them particularly good, and there are substantially better options now than there were not long ago. I would never, ever use it by choice.
Eh you don’t even need to go through all the trouble building a startup. imo Neon was interesting and filled a niche while open source solutions were really gaining maturity and adoption. Now they have, lots and lots of recommendations in this comment section, so my sense is that building a startup would be like reinventing the Neon wheel, just too late. Perhaps, depending on licensing, running OSS as a software is viable.
If you come up with the answers to some of these questions, I'd definitely read those blog articles on how you came to those conclusions. Keep asking interesting questions! Cheers
* No persist(). Not being able to cache dataframes is a nightmare when it's a workflow that involves taking a massive source of data, doing some rough filtering on it that gets it down to a tiny subset, and then doing more complex stuff with that.
* No good way to get usage info programmatically that I've found. For things like monitoring for periodic queries that get out of hand.
* Can't set Spark config. There are often ways to get around this, like when I recently had to set S3A credentials and needed a way that wasn't OS environment variables (this doesn't work for worker nodes). Eventually, through much documentation browsing and finally an exasperated hail mary question to ChatGPT that solved it (told me the things to pass into options() ) I got it working. But all the documentation and online QA resources just say to use Spark config.
* This is more of a Unity Catalog problem, but kind of applies because Serverless and UC often go very hand in hand (particularly when dealing with things that used to be stored in a cluster like credentials), but it drives me insane that I can only mount external volumes with the same block storage as my workspace provider. So I can't mount an external volume to an AWS bucket on an Azure UC. That means if I want to write stuff that can run the same regardless of what my customer is running their Databricks workspace with, I need to use less sophisticated approaches.
It's still nowhere near the pain that Databrick's attempt at copying Snowflake's VARIANT data type has caused me, but there are many times when I find myself having to work around serverless limitations. Especially when these limitations aren't really mentioned much upfront when Databricks pushes serverless aggressively.
TBH it's really quite boring. You just have to go back in time to the late 2010s. They had an excellent Spark-as-a-Service product, at a time when you'd have better luck finding a leprechaun than a reliable self-hosted Spark instance in an enterprise environment. That was simply beyond the capabilities of most enterprise IT teams at the time. The first-party offerings from the hyperscalars were relatively spartan.
Databricks' proprietary notebook format that introduced subtle incompatibilities with Jupyter was infuriating embrace-extend-extinguish style bullshit, but on-prem cluster instability causing jobs to crash on a daily basis was way more infuriating, and at that time, enterprises were more than happy to pay a premium to accelerate analytics teams.
In the 2010s, Databricks had a solid billion-dollar business. But Spark-as-a-Service by itself was never going to be a unicorn idea. AWS EMR was the giant tortoise lurking in the background, slowly but surely closing the gap. The status quo couldn't hold, and who doesn't want to be a unicorn? So, they bloated the hell out of the product, drank that off-brand growth-hacker Kool-Aid, and started spewing some of the most incoherent buzz-word salad to ever come out of the Left Coast. Just slapping data, lake, and house onto the ends of everything, like it was baby oil at a Diddy Party.
Now, here we are in 2025, deep into the terminal decline of enshittification, and they're just rotting away, waiting for One Real Asshole Called Larry Ellison to scoop them up and take them straight to Hell. The State of Florida, but for Big Data companies.
It would be a mystery to me too, why anyone would pick Databricks today for a greenfield project, but those enterprises from 5+ years ago are locked in hard now. They'll squeeze those whales and they'll shit money like a golden goose for a few more years, but their market share will steadily decrease over the next few years.
It's the cycle of life. Entropy always wins. Eventually the Grim Reaper Larry comes for us all. I wouldn't hate on them too hard. They had a pretty solid run.
Guess this is the beginning of the end of a great service, not holding my breath. Sounds like from the WSJ article that they’ll just become some AI agent backend service for Replit, and from the previous conversation on HN that Databricks ruins and shutters their acquisitions. Congrats on the big payout for the employees, though.
As it happens, we've just launched our new Xata platform (https://xata.io/) which has some of the key Neon features: instant copy-on-write branching and separation of storage and compute. As an extra twist, we also can do anonymization (PII masking) between your production database and developer branches.
The way we do copy-on-write branches is a bit different. We haven't done any modifications to Postgres but do it completely at the storage layer, which is a distributed system in itself. This also brings some I/O performance opportunities.
While Xata has been around for a while, we're just launching this new platform, and it is in Private Beta. But we are happy to work with you if you are interested.
Several components are open source as their own projects (see below) which will allow you to reproduce most of the features on top of regular Postgres. But the storage part is not open source. We are considering a simpler implementation of it that would be realistic to self-host and still do copy-on-write branching.
These are the open source components:
* pgstream for the anonymization from the production branch
I think when people look at Neon, the Aurora-style disaggregated compute/data architecture allowing highly scalable read replicas on cloud storage is the defining feature, and it's the only such project that offers it for Postgres. So the storage part is the point.
The PII masking aspect is very interesting and something we couldn't get when we decided on DBLab a month ago. What does the deployment model within AWS look like?
If you want to deploy the whole platform inside your own AWS account, we have a Bring Your Own Cloud model: https://xata.io/byoc
If you want to get anonymization from your RDS/Aurora instance and into Xata branches, then you run only a CLI command (`xata clone`) which does something similar to pg_dump/pg_restore but with masking. It is based on our pgstream open source project.
(Disclaimer: I work at Xata.)
Just wanted to mention that we also support anonymization, in case that’s something you're looking into:
https://xata.io/postgres-data-masking
Do you support http or websocket connections like https://github.com/neondatabase/serverless? In my experience neon is ultra fast that way in serverless environments like 1-5ms per query with network roundtrip.
1. Would you sign BAA (for HIPAA) for the Pay As You Go plan? Can't find that anywhere on your site except for that Lite is HIPAA compliant (https://lite.xata.io/security).
2. FYI, couldn't request access via the BYOC form so I sent an email as per the error: There was an error, please try again or contact us at info@xata.io.
Hi @tudorg - do the Xata copy-on-write branches work like Neon in that you effectively get an isolated Postgres cluster, allowing you to test roles, extensions, creating/dropping DBs, altering schema & data of existing DBs, etc? I looked in the docs but it wasn’t clear to me.
Yes, exactly, you get a new isolated Postgres database, just started from essentially a snapshot at the time of the fork. You can test any types of changes.
If all you care about is the forking aspect we use DBLab Engine pretty effectively: https://postgres.ai/products/dblab_engine. Gets deployed within your own infrastructure.
I remember the first post by the Neon team here on HN. I think I commented at the time that I thought it was a great idea. I’ve never had a need to use them yet, but thought I always would.
Cynically, am I the only one who takes pause because of an acquisition like this? It worries me that they will need to be more focused on the needs of their new owners, rather than their users. In theory, the needs should align — but I’m not sure it usually works out that way in practice.
Taking a pause also... I don't believe serving IA can be aligned to serving devs. I hope that the part of the work related to the core of PostgreSQL will help the community.
> I remember the first post by the Neon team here on HN. I think I commented at the time that I thought it was a great idea.
Same! I remember it too. I found it quite fascinating. Separation of storage and compute was something new to me, and I was asking them about Pageserver [0]. I also asked for career advice on how to get into database development [1].
Two years later, I ended up working on very similar disaggregated storage at Turso database.
Congratz to neon team (i like what they built), but i don’t see the value or relation to databricks. I hope neon will continue as a standalone product, otherwise we lose a solid postgres provider from the market.
Its pretty heavy in Azure, so I would be surprised if it went away. This is DBX play to move into the transactional database space in addition to the analytical database.
I really do hope that their OSS strategy does not change due to this, as it's really friendly to people who want to learn their product and run smaller deployments. It's (intentionally or not) really hard to run at a big scale as the control plane is not open-source, which makes the model actually work.
Databricks is Oracle-level bad. They will definitely ruin Neon or make it expensive. In the medium to long term, I will start looking for Neon alternatives.
Definitely agree, their M&A strategy is setup to strangle whoever they buy and they don't even know it. They're struggling in the face of Iceberg, DuckDB and the other tectonic shifts happening in the open source world. They are trying to innovate through acquisition, but can't quite make it because their culture kills the companies they buy.
I'm biased, I'm a big-data-tech refugee (ex-Snowflake) and am working on https://tower.dev right now, but we're definitely seeing the open source trend supported by Iceberg. It'll be really interesting to see how this plays out.
To be honest this is a little sad for me. I'd hoped that Neon would be able to fill the vacuum left by CockroachDB going "business source"
Being bought by DataBricks makes Neon far less interesting to me. I simply don't trust such a large organisation that has previously had issues acquiring companies, to really care about what is pretty much the most important infrastructure I've got.
There certainly is enough demand for a more "modern" postgresql, but pretty much all of the direct alternatives are straying far from its roots. Whether it be pricing, compatibility, source available etc.
Back when I was looking at alternatives to postgres these were considered:
1. AWS RDS: We were already on AWS RDS, but it is expensive, and has scaling and operations issues
2. AWS Aurora: The one that ended up being recommended, solved some operations issues, but came with other niche downsides. Pretty much the same downsides as other wire compatible postgresql alternatives
3. CockroachDB: Was very interesting, wire compatible, but had deeper compatibility issues, was open source at the time, it didn't fit with our tooling
4. Neon: Was considered to be too immature at the time, but certainly interesting, looked to be able to solve most of our challenges, maybe except for some of the operations problems with postgresql, I didn't look deeper into it at the time
5. Yugabyte: interesting technology, had some of the same compatibility issues, but less that the others, as they're also using the query engine from postgresql as far as I can tell.
There are also various self hosting utilities for PostgreSQL I looked at, specifically CloudPG, but we didn't have the resources to maintain a stateful deployment of kubernetes and postgres ourselves. It would fulfill most of our requirements, but with extra maintenance burden, both for Kubernetes and PostgreSQL.
Hosting PostgreSQL by itself, didn't have mature enough replication and operations features by itself at that point. It is steadily maturing, but as we'd got many databases manual upgrades and patches would be very time consuming, as PostgreSQL has some not so nice upgrade quirks. You basically have to unload and reload all data during major upgrades. Unless you use extensions and other services to circumvent this issue.
Mainly in relation to notify/listen and advisory locks. Most of our code bases use advisory lock based migration tools. It would be a large lift moving to an alternative or building a migration scheduler out of process
> 5. Yugabyte: interesting technology, had some of the same compatibility issues, but less that the others, as they're also using the query engine from postgresql as far as I can tell.
In my brief experience as an engineer (2014->), I've learned that the best "modern" alternative to PostgreSQL at year X has been PostgreSQL at year X+5. :)
Hey everyone, I'm an engineer at Neon and I wanted to share this FAQ which covers a lot of the questions that are being brought up in the comments here:
That’s a nice FAQ and all but after what happened to bit.io [0] you have to understand why people (like me) are extremely worried about this.
We’ve all read glowing blog posts and reassuring FAQs enough times after an acquisition only to see a
complete about-face a few months or a year later.
I quite enjoyed using Neon but as a solo founder running my business on Neon I can’t help but think it’s insanity to not be looking for alternatives.
Databricks is _not_ a company I trust at all.
[0] if you don’t know, databricks acquired bit.io and shut down all databases within 30 days. Production databases had <30 days to migrate.
For what it's worth the questions can't really be answered by a simple FAQ, because history has shown that those answers aren't worth the page they're written on. Many companies that get bought talk all about the fact that nothing is going to change.
Something is always going to change, almost always in a way that impacts customers. In the best case it's something simple like a different name on the bill, other times it will leave customers scrambling for an alternative before a ridiculous deadline. It could happen within weeks, after a month, or it might take a year. The answers at the time of the announcement are the same regardless.
Love Neon, but that FAQ is worthless. Every company that gets acquired reassures customers that "nothing will change"... then it does, once the new company is in the acquirer's belly and gets digested.
Most likely a holding state for a bit before databricks ruins it or shuts it down. I started looking around when the news broke last week or so for alternatives.
Supabase is one that I'll consider, Xata [0] is another one that is interesting. Thankfully I just need "postgres", I don't need branching/PII-clearing/etc. That's all nice to have but I don't need it for my app.
I really would prefer a managed DB for multiple reasons but I might need to look at just self-hosting. I might have spent less time futzing with my DB if I had done that from the start instead of going Aurora Serverless v1 -> Planetscale -> Neon.
I believe that, it's a cool concept. But I was too nervous to build on top of that feature, I wanted to maintain my ability to leave Neon easily. After Planetscale (and using their version of schema branching) I didn't want to get pinched again when I went to switch (PS vs Neon branching was/is very different).
I think one of the coolest features of neon is being able to quickly spin up new DBs via the API (single tenant DBs) and while that is cool, my client list is small so manually creating the DBs is not a problem (B2B).
I applied to neon last week and then the news broke about the acquisition. They rejected it this morning — I have never been happier to receive a rejection to an application.
This would’ve been three acquisitions straight for me and… I’m okay, they’re awful. I just want stability.
Congrats to the neon team! I use and love neon. Really hope this doesn’t change them too much.
I got hired at Kenna Security a month before they were acquired by Cisco and it was such a miserable experience that I won't work for any company the Kenna leadership are involved with, nor would I ever consider working at Cisco.
I've been through two now, and for one of them nothing much changed, and the other one I was basically lost in a stack of papers for a year. Can I ask what made the experience miserable for you?
The first acquisition I was apart of wasn’t too bad! But we were still culturally very different. So after 2 years and properly transitioning things, I bounced to another start up.
Walking into something like that is tough because the two teams sort of don’t like each other and you’re really “neither”. I’d want to make sure I was interviewed by both teams
I was a very early employee at the other two start ups that were acquired and even with equity it was not worth it. After all the class A shares were paid out, the rest of us got little.
I mean, hindsight 20/20 here, but I would have loved the theoretical money @ 1 billion. But those are so rare and my experience in the past 15 years hasn’t matched those unicorns.
Basically I’ve come to the conclusion unless you have serious equity or you’re a founder, acquisition suck. You’re the one doing the work making these two companies come together, while the founders usually bounce or are stripped of any real power to change things.
Yes, that is what i expect, too. They have been paying DynamoDB and CosmosDB for a few years now. However, Neon is not competitive latency/throughput-wise for real-time workloads, needed for high end AI (like personalized recommendations). There are a few others I would have expected like Cockroach, Aerospike, or RonDB.
I've been part of an acquisition as a first-year engineering manager, during which I had to navigate subsequent two rounds of layoffs. I was also a part of the group to help restructure teams and help make calls on who to keep. Morale was terrible, and the cultures also did not gel at all.
It led to some serious burnout and I took several months off. I'm now happily working as an IC again.
I’m incredibly disappointed by this news. I really enjoyed Neon but I seriously doubt I’m going to like Databricks’ stewardship if it. And that’s if they even still care about catering to people like me and don’t jack the prices us.
I guess it’s time to go back to the well of managed/serverless Postgres options…
Crazy how big the data ecosystem has grown. Congrats to the Neon team on a good outcome, but good luck integrating into DBX culture and surviving.
I'm seeing a lot of DBX hate in this thread overall. I think it's warranted. At Tower[0], we're trying to provide a decent open solution. It stars with owning your own data, and Iceberg helps you break free.
It's big, enterprise, and competes aggressively on marketing and hype. Also there have been a string of acquisitions where databricks has kind of just absorbed the team and product and then not done a great job for customers of the old company.
It's fine. Probably actually a good place to work.
If you're someone who researched the company, enjoyed the interview and accepted an offer, you're probably not going to be in the same group as the people who hate Databricks. Databricks is a 10k people enterprise software company that just raised $10bn and is using their deep pockets to hoover up smaller companies. If that doesn't scare you, you'll be fine. For many of us, the thought of working with or using the product of a company like that strikes fear into our hearts because we have different values to you.
Databricks is the antithesis of Neon. Neon is driven by product, Databricks is driven by sales. Opinions of Databricks in a thread about Neon are going to be on the negative side (but not necessarily representative).
I've been an SA at Databricks for the past two years and love it here. The people you get to work with here are world-class and our customers legitimately love our product.
I too am a little confused about comments in threads on HN about Databricks, they seriously don't reflect what I see internally and what my customers say. I don't think I'd be working here if they did.
It's my understanding that Neon had some tech to basically "wake up" the DB when a request came out -- so you could "scale down to zero," if you will. I was hoping to explore this for small personal projects: I by far prefer Postgres and would love an isolated database per project.
Is there an alternative for that? Scale-to-zero postgres, basically?
AWS Aurora is way too expensive and their "serverless" offerings are overly complicated and not worth it IMHO.
I used Serverless v1 and then they doubled the prices for v2 while removing features so I moved to PlanetScale. They were great but as I grew and wanted multiple smaller DBs they didn't really have a good way to do that and I moved to Neon. Now, with this news, I guess I'll be looking for an alternative.
> AWS Aurora Postgres Serverless v2 has that capability
Was just about to react to someone being wrong on the internet and say that this is not true. Instead, TIL that this is, in fact, the case. Since 2024Q4.
For small personal projects, coolify (featured recently here on HN) lets you quickly stand up postgres with SSL, etc. and get a connection string in seconds. You can deploy in the same project or expose pg to the world like neon does.
One click turns it off, or you can just leave it on. A $5 VM will run a lot of small postgres.
I use both neon and coolify, and could live with either, though apples and oranges when it comes to the data branching feature. But a quick pg_dump/restore which could even be scripted solves my problem. Disclaimer: I like devops in addition to just dev.
I'm not afraid of running servers, that was not the point. The point was exactly that I wanted a serverless postgres.
If I can throw together a random project, completely isolated, that costs $0.10 per month, that enables me to do many orders more random projects than something that costs me $5 per month.
Does anyone have insight into Neon's financials - specifically their revenue, COGS, and gross margins? I'm trying to understand what made Databricks value them at $1B. Was it strong unit economics, rapid growth, or mostly strategic/tech value?
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[ 2.2 ms ] story [ 245 ms ] threadWSJ article: https://www.wsj.com/articles/databricks-to-buy-startup-neon-...
Today it suffers from feature creep and too many pivots & acquisitions. That they are insanely bad at naming features doesn't help either.
The biggest gripe in have is how crazy expensive it is.
But these days just use trino or whatever. There are lots of new ways to work on data that are all bigger steps up - ergonomically, performance and price - over spark as spark was over hadoop.
What an impressive feat of engineering.
Can't imagine someone incapable of building a website would deliver a good (digital) product.
The product is still centered Spark, but most companies don't want or need Spark and a combination of Iceberg and DuckDB will work for 95% of companies. It's cheaper, just as fast or faster and way easier to reason about.
We're building a data platform around that premise at Definite[0]. It includes everything you need to get started with data (ETL, BI, datalake).
0 - https://www.definite.app/
There are some examples[0] of enabling DuckDB to manage distributed workloads, but these are pretty experimental.
0 - https://www.definite.app/blog/smallpond
I really don't understand the valuation for this company. Why is it so high.
But if you're inclined to use it, databricks' setup of spark just saves you an incredible amount of time that you'd normally waste on configuration and wiring infrastructure (storage, compute, pipelines, unified access, VPNs etc). It's expensive and opinionated, but the data engineers you need to deal with spark OOM errors constantly is greater. Also databricks' default configs give you MUCH better performance out of the box than anything DIY and you don't have to fiddle with partitions and super niche config options to get even medium workloads stable
What are some bad UX choices you generally dislike in data products?
* No persist(). Not being able to cache dataframes is a nightmare when it's a workflow that involves taking a massive source of data, doing some rough filtering on it that gets it down to a tiny subset, and then doing more complex stuff with that.
* No good way to get usage info programmatically that I've found. For things like monitoring for periodic queries that get out of hand.
* Can't set Spark config. There are often ways to get around this, like when I recently had to set S3A credentials and needed a way that wasn't OS environment variables (this doesn't work for worker nodes). Eventually, through much documentation browsing and finally an exasperated hail mary question to ChatGPT that solved it (told me the things to pass into options() ) I got it working. But all the documentation and online QA resources just say to use Spark config.
* This is more of a Unity Catalog problem, but kind of applies because Serverless and UC often go very hand in hand (particularly when dealing with things that used to be stored in a cluster like credentials), but it drives me insane that I can only mount external volumes with the same block storage as my workspace provider. So I can't mount an external volume to an AWS bucket on an Azure UC. That means if I want to write stuff that can run the same regardless of what my customer is running their Databricks workspace with, I need to use less sophisticated approaches.
It's still nowhere near the pain that Databrick's attempt at copying Snowflake's VARIANT data type has caused me, but there are many times when I find myself having to work around serverless limitations. Especially when these limitations aren't really mentioned much upfront when Databricks pushes serverless aggressively.
Databricks' proprietary notebook format that introduced subtle incompatibilities with Jupyter was infuriating embrace-extend-extinguish style bullshit, but on-prem cluster instability causing jobs to crash on a daily basis was way more infuriating, and at that time, enterprises were more than happy to pay a premium to accelerate analytics teams.
In the 2010s, Databricks had a solid billion-dollar business. But Spark-as-a-Service by itself was never going to be a unicorn idea. AWS EMR was the giant tortoise lurking in the background, slowly but surely closing the gap. The status quo couldn't hold, and who doesn't want to be a unicorn? So, they bloated the hell out of the product, drank that off-brand growth-hacker Kool-Aid, and started spewing some of the most incoherent buzz-word salad to ever come out of the Left Coast. Just slapping data, lake, and house onto the ends of everything, like it was baby oil at a Diddy Party.
Now, here we are in 2025, deep into the terminal decline of enshittification, and they're just rotting away, waiting for One Real Asshole Called Larry Ellison to scoop them up and take them straight to Hell. The State of Florida, but for Big Data companies.
It would be a mystery to me too, why anyone would pick Databricks today for a greenfield project, but those enterprises from 5+ years ago are locked in hard now. They'll squeeze those whales and they'll shit money like a golden goose for a few more years, but their market share will steadily decrease over the next few years.
It's the cycle of life. Entropy always wins. Eventually the Grim Reaper Larry comes for us all. I wouldn't hate on them too hard. They had a pretty solid run.
As it happens, we've just launched our new Xata platform (https://xata.io/) which has some of the key Neon features: instant copy-on-write branching and separation of storage and compute. As an extra twist, we also can do anonymization (PII masking) between your production database and developer branches.
The way we do copy-on-write branches is a bit different. We haven't done any modifications to Postgres but do it completely at the storage layer, which is a distributed system in itself. This also brings some I/O performance opportunities.
While Xata has been around for a while, we're just launching this new platform, and it is in Private Beta. But we are happy to work with you if you are interested.
Btw, congrats to the Neon team!
These are the open source components:
* pgstream for the anonymization from the production branch
* pgroll for schema changes
* Xata Agent for the LLM-powered optimizations
If you want to get anonymization from your RDS/Aurora instance and into Xata branches, then you run only a CLI command (`xata clone`) which does something similar to pg_dump/pg_restore but with masking. It is based on our pgstream open source project.
Happy to organize a demo any time.
(Disclaimer: I work at Xata.) Just wanted to mention that we also support anonymization, in case that’s something you're looking into: https://xata.io/postgres-data-masking
2. FYI, couldn't request access via the BYOC form so I sent an email as per the error: There was an error, please try again or contact us at info@xata.io.
2. Thanks, I see you sent the email already, not sure why it failed. Will reach out over email.
Cynically, am I the only one who takes pause because of an acquisition like this? It worries me that they will need to be more focused on the needs of their new owners, rather than their users. In theory, the needs should align — but I’m not sure it usually works out that way in practice.
Same! I remember it too. I found it quite fascinating. Separation of storage and compute was something new to me, and I was asking them about Pageserver [0]. I also asked for career advice on how to get into database development [1].
Two years later, I ended up working on very similar disaggregated storage at Turso database.
Congrats to the Neon team!
[0] - https://news.ycombinator.com/item?id=31756671
[1] - https://news.ycombinator.com/item?id=31756510
I really do hope that their OSS strategy does not change due to this, as it's really friendly to people who want to learn their product and run smaller deployments. It's (intentionally or not) really hard to run at a big scale as the control plane is not open-source, which makes the model actually work.
I'm biased, I'm a big-data-tech refugee (ex-Snowflake) and am working on https://tower.dev right now, but we're definitely seeing the open source trend supported by Iceberg. It'll be really interesting to see how this plays out.
To be honest this is a little sad for me. I'd hoped that Neon would be able to fill the vacuum left by CockroachDB going "business source"
Being bought by DataBricks makes Neon far less interesting to me. I simply don't trust such a large organisation that has previously had issues acquiring companies, to really care about what is pretty much the most important infrastructure I've got.
There certainly is enough demand for a more "modern" postgresql, but pretty much all of the direct alternatives are straying far from its roots. Whether it be pricing, compatibility, source available etc.
Back when I was looking at alternatives to postgres these were considered:
1. AWS RDS: We were already on AWS RDS, but it is expensive, and has scaling and operations issues
2. AWS Aurora: The one that ended up being recommended, solved some operations issues, but came with other niche downsides. Pretty much the same downsides as other wire compatible postgresql alternatives
3. CockroachDB: Was very interesting, wire compatible, but had deeper compatibility issues, was open source at the time, it didn't fit with our tooling
4. Neon: Was considered to be too immature at the time, but certainly interesting, looked to be able to solve most of our challenges, maybe except for some of the operations problems with postgresql, I didn't look deeper into it at the time
5. Yugabyte: interesting technology, had some of the same compatibility issues, but less that the others, as they're also using the query engine from postgresql as far as I can tell.
There are also various self hosting utilities for PostgreSQL I looked at, specifically CloudPG, but we didn't have the resources to maintain a stateful deployment of kubernetes and postgres ourselves. It would fulfill most of our requirements, but with extra maintenance burden, both for Kubernetes and PostgreSQL.
Hosting PostgreSQL by itself, didn't have mature enough replication and operations features by itself at that point. It is steadily maturing, but as we'd got many databases manual upgrades and patches would be very time consuming, as PostgreSQL has some not so nice upgrade quirks. You basically have to unload and reload all data during major upgrades. Unless you use extensions and other services to circumvent this issue.
I'm interested if you'd care to elaborate.
Neon is Postgres.
https://neon.tech/databricks-faq
We're really excited about this, and will try to respond to some of the questions people have here later.
We’ve all read glowing blog posts and reassuring FAQs enough times after an acquisition only to see a complete about-face a few months or a year later.
I quite enjoyed using Neon but as a solo founder running my business on Neon I can’t help but think it’s insanity to not be looking for alternatives.
Databricks is _not_ a company I trust at all.
[0] if you don’t know, databricks acquired bit.io and shut down all databases within 30 days. Production databases had <30 days to migrate.
Something is always going to change, almost always in a way that impacts customers. In the best case it's something simple like a different name on the bill, other times it will leave customers scrambling for an alternative before a ridiculous deadline. It could happen within weeks, after a month, or it might take a year. The answers at the time of the announcement are the same regardless.
Most likely a holding state for a bit before databricks ruins it or shuts it down. I started looking around when the news broke last week or so for alternatives.
I really would prefer a managed DB for multiple reasons but I might need to look at just self-hosting. I might have spent less time futzing with my DB if I had done that from the start instead of going Aurora Serverless v1 -> Planetscale -> Neon.
[0] https://xata.io/
I think one of the coolest features of neon is being able to quickly spin up new DBs via the API (single tenant DBs) and while that is cool, my client list is small so manually creating the DBs is not a problem (B2B).
https://news.ycombinator.com/item?id=43899016
Databricks in talks to acquire startup Neon for about $1B (174 comments)
This would’ve been three acquisitions straight for me and… I’m okay, they’re awful. I just want stability.
Congrats to the neon team! I use and love neon. Really hope this doesn’t change them too much.
In a couple cases I’ve been recruited because I have a history of scaling and integrating acquisitions into companies successfully
Walking into something like that is tough because the two teams sort of don’t like each other and you’re really “neither”. I’d want to make sure I was interviewed by both teams
IMO, this is where the power of being hired into the situation is. No existing bias for either company and all the baggage that comes with that.
Allows a person to see the pros and cons of how things get done on both sides of the fence, and act accordingly
I mean, hindsight 20/20 here, but I would have loved the theoretical money @ 1 billion. But those are so rare and my experience in the past 15 years hasn’t matched those unicorns.
Basically I’ve come to the conclusion unless you have serious equity or you’re a founder, acquisition suck. You’re the one doing the work making these two companies come together, while the founders usually bounce or are stripped of any real power to change things.
My guess is that this team gets rolled into Online Tables tech, which would make product sense.
https://docs.databricks.com/aws/en/machine-learning/feature-...
It led to some serious burnout and I took several months off. I'm now happily working as an IC again.
Surely, there might be other agents creating Neon databases so we might be under-counting.
I guess it’s time to go back to the well of managed/serverless Postgres options…
I'm seeing a lot of DBX hate in this thread overall. I think it's warranted. At Tower[0], we're trying to provide a decent open solution. It stars with owning your own data, and Iceberg helps you break free.
[0] - https://tower.dev
It's fine. Probably actually a good place to work.
Databricks is the antithesis of Neon. Neon is driven by product, Databricks is driven by sales. Opinions of Databricks in a thread about Neon are going to be on the negative side (but not necessarily representative).
I've been an SA at Databricks for the past two years and love it here. The people you get to work with here are world-class and our customers legitimately love our product.
I too am a little confused about comments in threads on HN about Databricks, they seriously don't reflect what I see internally and what my customers say. I don't think I'd be working here if they did.
I like how they’re innovating, but it can be rough around the edges sometimes.
Is there an alternative for that? Scale-to-zero postgres, basically?
I used Serverless v1 and then they doubled the prices for v2 while removing features so I moved to PlanetScale. They were great but as I grew and wanted multiple smaller DBs they didn't really have a good way to do that and I moved to Neon. Now, with this news, I guess I'll be looking for an alternative.
Was just about to react to someone being wrong on the internet and say that this is not true. Instead, TIL that this is, in fact, the case. Since 2024Q4.
Thanks for invalidating my stale cache.
One click turns it off, or you can just leave it on. A $5 VM will run a lot of small postgres.
I use both neon and coolify, and could live with either, though apples and oranges when it comes to the data branching feature. But a quick pg_dump/restore which could even be scripted solves my problem. Disclaimer: I like devops in addition to just dev.
If I can throw together a random project, completely isolated, that costs $0.10 per month, that enables me to do many orders more random projects than something that costs me $5 per month.
This seems like quite the pivot though