1,265 karma · joined May 26, 2010
On a somewhat related note, the reason why Peugeot cars have a "0" in their model numbers (e.g. 208, 308, 408, etc.) goes back to the days before electric ignition, and when you still needed a crank to start the engine. The model number was in the middle of the grill, and the crank would go into the "0".
https://github.com/someengineering/fixinventory
I'm one of the people behind Fix Inventory. What scares a lot of developers away from graph-based tools is the graph query language. It has a steep learning curve, and unless you write queries every day, it's really cumbersome to learn.
We simplified that with our own search syntax that has all the benefits of the graph, but simplified a few concepts like graph traversal.
I think the support model worked once, exactly once, and that was for Red Hat.
Not saying that you can't charge for support, but the days of building a company on support fees are long gone.
I've built analytics products, and the good thing about dashboards is that there's budget for them. People like eye-candy, and are willing to pay for it. I like how you picked Postgres as your initial database, because I think it's still the #1 databases for analyics (even though it's OLTP) that no one talks about.
The three products where I think you may want to write short comparison pages are:
- Rill - Preset - Metabase
And I'd take a hard look at ClickHouse as your next database. They're missing a dashboard partner. And I think they're users are much more engineering-centric and therefore a good fit for you than the analytics crowd around Snowflake.
https://resoto.com/defrag https://github.com/someengineering/resoto
The magic behind the clean up is Resoto's inventory graph - the graph captures the clean up steps for each individual AWS resource.
One of Resoto's users, D2iQ (now part of Nutanix), reduced their monthly cloud bill by ~78%, decreased from $561K to $122K per month. There's a step-by-step tutorial on our blog how they did it.
I don't mean to hijack Dashdive's thunder here though, congrats on the launch!
The important piece of that vendor contract however was the integration with the point-of-sale system of each liquor shop. That's how Drizly knew what was on the shelf, and was able to sell inventory.
Drizly was one of our customers at my earlier company where I learned about these integrations. The world of POS systems is highly fragmented and arcane - there's no one system.
One asset that Drizly had developed was an integration platform that connected to any possible POS any of the liquor stores were using. No one else had done that. They just kept chipping away at it. Literally every sprint, they'd add more integrations. I believe the goal was 2 integrations per sprint. That includes data model, etc. to create the analytics downstream.
That integration platform was almost something like a natural monopoly. Hard to replicate by another party.
The core of the answer was that cloud warehouses are not suitable for real-time use cases, because the batch processing and transformations take too long. If you want real-time, you need to pay up - hence Databricks / Spark. I did call out the fraud use case in that answer.
There were 1st generation ETL tools like Alooma that tried to go into the direction of streaming, and they pushed the limits.
Back then (we had built cloud warehouse monitoring tool), the closest to real-time I've ever seen any company get was IronSource. The time between an event and until that event was available in a dashboard was five minutes (they were using Redshift).
I'll stick my neck out and say that certain industries will be all over Artie, whereas others will shrug their shoulders.
The industries that I think will be all over Artie:
- FinTech - Insurance - AdTech - Gaming - Publishing - Logistics / Delivery
These are industries where a couple of minutes of difference in data recency can make a difference of millions of dollars. And you'll probably cost less than existing streaming solutions, which is obviously nice. But I think the real advantage will be simplicity.
I know you can't support all destinations at once, and need to go with where demand is. But I would expect that the Materialize and Clickhouse crowds are good target users for you.
Good luck, this is an exciting product!
Quite a bit of that area is already water (the Delta), and we've seen during the heavy rains during 2017 (the period the article refers to) how the land around it can take a lot of flooding.
I've driven down the road from the dam to Winters, and the chutes I think would act like a giant water cannon. I wouldn't have high hopes for Winters. Driving down that road, I kept thinking "why would anyone buy real estate here?" - yet people do.
Three years ago, I overheard a conversation of three CalFire employees on the way up to Tahoe.
The topic of the discussion was that "some" fire is desirable. And then I remember what the Chief said, and I'm roughly paraphrasing - "People tend to forget that CalFire's charter is to extinguish fires. [...]", and then hinting that unless that charter changes, more fuel will build up over time.
5,168 "Base Customers": Customers generating $5,000 or more in ARR. 545 "$100K customers": Customers generating $100,000 or more in ARR
Compared to a year ago (Q1-FY22):
Base Customers: 3,142 --> 5,168 $100K Customers: 324 --> 545
$350M run-rate revenue in Q1 FY23, up from $200M in Q1 FY22.
https://larskamp.medium.com/picking-an-open-source-license-a...
Apache 2.0 is the dominant license at this point, mainly because to foster adoption.
The whole scare about the clouds ripping you off, like it happened with Elastic, is not really valid anymore. The clouds have learned that it's better to cooperate.
Link to the repo in my HN profile.