When editing the launch blurbs, I usually tell founders to add explanations of any concepts or jargon that HN readers might not be familiar with. It's not always easy to know where to draw that line.
https://news.ycombinator.com/item?id=33360234 was pretty rightly flagged though - you're not supposed to put down other people's work in HN threads, especially not Launch or Show HN threads (https://news.ycombinator.com/showhn.html).
I asked about some terms and if they are common among the HN crowd. Ako replied that people who are doing enterprise software integrations know them. Then I ask if the HN crowd is nowadays people who are doing enterprise software integrations. (Because that is not what I would associate with hackers / startup founders. So maybe what initially was a community of hackers + startup founders is now a community of grown ups with enterprise jobs.)
Whose work have I put down by asking this?
If you say that wasn't your intent, I believe you, but I doubt that I'm the only reader who took things that way. It can be difficult to read intent accurately from short internet comments. Ultimately the burden is on the commenter to disambiguate intent (https://hn.algolia.com/?dateRange=all&page=0&prefix=false&so...).
To be honest I still find it hard to read that comment and not feel that it was being snide. If one takes your question at face value, it answers itself: of course the community is not "about that"—it's got all sorts of people doing all sorts of things.
Have curious conversation; don't cross-examine.
Data connectors, in the loosest definition possible, is simply a piece of software that moves data from one place to the other. This can be from database A to database B or (as in our case) from a given API into a database.
ETL stands for "Extract, Transform, Load", a process in which you get data from some place, clean it/do something with it, then store it into a desired destination. Probably this term is most frequently used in the context of data warehousing, in which you move data from one or more OLTP databases from the application side, into an OLAP database.
Finally, Snowflake is a very popular (and very cool) database focused on Data Warehousing needs.
I get kind of a "no code" vibe from it?
When I want to read data from an API, transform it and put it into a DB, my approach would be to write a few lines of Python. A script that does an http request to the API, transforms it and then writes the data to SQLite.
That seems much easier and more future proof to me than to bring in a 3rd party service.
Google probably has better explanations for these, but to summarize:
* data connectors - connectors that allow you to get data from all systems you use in your organization, from databases to ERPS, to custom build systems.
* ETL - a method for moving data from your data sources to your datawarehouses (DWH) - extract from source, transform to desired format, load in you DWH.
* Snowflake - cloud based highly scalable DWH for structured and unstructured data