Datalore enterprise – Jupyter environment for data science teams
blog.jetbrains.com
blog.jetbrains.com
What makes Jetbrain's iteration far better than any of the other competitors? So far nothing?
JetBrain is specialized in listening devs, code mining and smooth integration. It seems like a good match, at least in my head :)
I'm not really getting excited over this, sadly.
It's an enterprise-branded product, but nothing in this product stops people from writing the same old spaghetti. Then it's up to the engineers to figure out a way to get the spaghetti to behave.
I'd rather see some dev platform that forces an analyst or data scientist to think about integrating with other infrastructure in a sane way. Your code, conformed and embedded into some CI/CD pipeline. easy to set up data pipelines. unit/integration/data integrity test boilerplate generators geared towards data science.
(I know I'm probably describing something that's impossible... one can dream)
Curently in private beta (just sign up for it, you'll get access).
[1] https://www.rstudio.com/products/rstudio/
edit: clarify
Must be JetBrains’ headline writers too, since the headline is “Announcing Datalore Enterprise – The Smart and Secure Jupyter Environment for Data Science Teams” making it sound rather like flowered up Jupyter.
Everything I've ever tried to use that plugged into Hub has been less excellent. I don't think I have the problems that's meant to solve. Our on-premise TeamCity server works just fine without it, and we never laid down the entire suite of other tools that would use Hub.
Other cloud offerings (besides Coalb) are more like a vanilla Jupyter. This one seems more customized. Not sure it's a good thing, but it's understandable as a JetBrains product.
I think Colab is indeed more comparable here. Overall Colab seems a bit better on available resources, but Datalore UI seems more powerful. Also, it seems to have R support. That can be a killer for would-be Colab users who aren't opted to Python.
- [1] https://datalore.jetbrains.com/
- [2] https://blog.jetbrains.com/blog/2018/10/17/datalore-1-0-inte...
I think compared to Jupyter Notebooks this can more directly solve a problem for anyone who wants to do analysis on customer data, historic log data, JIRA tickets, incidents, etc. The long-term goal for a commercial version would be to have high level connections to all the APIs developers use; to make cross-datasource analysis easier.
We have engineers in the thousands so that would be a budget in the millions per year, for a tool for which it's hard to demonstrate the productivity benefit over alternatives. Not going to happen.
It's not that the company can't afford it, but enterprises are strict when it comes to spending money. There are lots of processes, checks, and people that sign off.
Plenty of places pay X for tools that add more than X in productivity value.
In fact, nearly every tool I have ever gotten at a company worked like this. Most of them are also willing to test pricey tools to see if they would pay off, and when they do, the company starts buying such tools.
If you don't work at such a place, look for a place that values developer time.
Oh and noise cancelling headphones.
They infiltrated my college and got all of our students to use phpstorm for free. Upon graduation they smack you with a huge cost to continue.
I imagine quite a few grads didn't want to learn a new IDE.
0: https://www.jetbrains.com/phpstorm/buy/#personal?billing=yea...
1: https://www.jetbrains.com/phpstorm/buy/#commercial?billing=y...