14 karma · joined May 23, 2008
I love the idea of this tool.
This came just at the right time. I'm putting together a series of animations for patient education. In trying to make things cross-platform I had to resort to AE and non-interactive video. Lottie looks like it will enable me to string together something nicer, using native drawing functionality, and can incorporate more interactivity.
With such proliferation of self hosted FireBase, can anyone in the know share their experiences with these solutions?
For my applications in healthcare I'm often forced to use in-house servers.
I made some queries that are analogous to my temporal query needs
Here I'm looking for every student, other students with DOB within 2 weeks of the given student: http://demo.htsql.org/student.define(similar_students:=%20(s...
Here for every semester with at least one student, I find the oldest and the youngest students enrolled: http://demo.htsql.org/semester%20.define(starting_students:=...
No being a computer scientist I have to admit I do not appreciate the intricacies of the 'problems with SQL' blog entries. But working with htsql I gotta say it seems a lot more intuitive than SQL. It feels like the logic correspond much better to my mental model. And that there is much less of the jumping up and down the code to nest my SQL code logic that I find myself doing all the time.
Is there a way to install this on a PostgresQL instance on Win8?
how does htsql do with this?
Do you have more info on the introvert/extrovert link?
Source? I don't think this is the case
it seems that Android as a solution to the problem of a mobile phone is overshooting a big chunk of the market. in that sense I think FxOS is in a good position to disrupt the mobile space.
now how can I get my hands on a phone??
The problem with GAE as many have pointed out is being locked-in to the GAE architecture. I'm betting on open source systems built on top of AWS, specifically scalr. Can anyone comment on their experiences with scalr?
The perceived probability of "getting popular enough" is for most start-ups non-zero. Else many start-ups would not even exist at all. That is, the expected value of the entire start-up endeavor, E(start-up)--say in the unit of dollars--is driven by these rare, but extreme outcomes.
Given this is the case, my impression is that: P( failure to scale | RDBMS ) > P( failure to scale | BigTable/simpleDB ) (that is, it is much more difficult to scale up RDBMS than BigTable/SimpleDB)
and P( success | failure to scale ) is near 0,
then it makes sense to prepare for that possible rare outcome of having to scale, in order to preserve that expected value.