psarm VS crux

Thanks for the thoughtful response! Many of these are totally legitimate: in particular, we're making steady progress to centralize module design, release, documentation, and modernization, or at least to bring many teams closer together. In many cases, we're at a transition point between moving from traditional PS remoting modules and filling out PS coverage for newer OAuth / REST API flows.

I don't know how recently you've tried PS7, but the back-compat (particularly on Windows) is much, much better[1]. And for those places where compatibility isn't there yet, if you're running on Windows, you can just `Import-Module -UseWindowsPowerShell FooModule` and it'll secretly load out-of-proc in Windows PS.

Unfortunately, the .NET problems are outside my area. I'm definitely not the expert, but I believe many of the decisions around the default assembly load context are integral to the refactoring of .NET Core/5+. We are looking into building a generalized assembly load context that allows for "module isolation", and I'd love to get a sense in the issue tracking that[2] whether or not fixing that would help solve some of the difficulties you're having in building modules.

For Azure, you should check out the PSArm[3] module that we just started shipping experimentally. It's basically a PS DSL around ARM templates, as someone who uses PS and writes the Azure JSON, you sound like the ideal target for it.

As for the help content, that's a very funny story for another time :D

[1]: https://aka.ms/psmodulecompat

[2]: https://github.com/PowerShell/PowerShell/issues/2083

[3]: https://github.com/powershell/psarm

Hi, a couple of my colleagues spent some time working on this integration with our open source database product (https://opencrux.com), and I'm curious to know - has anyone done similar things to connect Corda with a secondary off-the-shelf query engine?

For more details, see the release notes.

The context is that I work on on https://opencrux.com, which offers a bi-temporal Datalog query layer (as well as SQL) that more or less addresses the intersection of the two, since Datalog is great for expressing recursive queries.

I suppose another somewhat important distinction, once again performance related, is that graph databases will typically track index statistics to aid with query planning. For example, Crux uses stored knowledge of attribute-value cardinalities (recently via HyperLogLog) to optimise the join order of a query - this can make a big difference when attempting to traverse large graphs efficiently.

Agreed, recursive querying & bitemporal modelling in SQL are non-trivial problems, and the combination of the two is harder still. For an alternative perspective on tackling such problems I'd suggest looking at Datalog, which makes recursion a breeze, and a database with first-class bitemporality - both of which feature in https://opencrux.com (which I happen to work on :))

I work on Crux so can share a few details about our implementation of Datalog. The query is compiled into a kind of Worst-Case Optimal Join algorithm [0] which means that certain types of queries (e.g. cyclic graph-analytical queries, like counting triangles) are generally more efficient than what is possible with a non-WCOJ query execution strategy. However, the potency of this approach relies on the query planner calculating a good ordering of variables for the join order, and this is a hard problem in itself.

Crux is usually very competent at selecting a sensible variable ordering but when it makes a bad choice your query will take an unnecessary performance hit. The workaround for these situations is to break your query into smaller queries (since we don't wish to support any kind of hinting). Over the longer term we will be continuing to build more intelligent heuristics that make use of advanced population statistics. For instance we are about to merge a PR that uses HyperLogLog to inform attribute selectivity: https://github.com/juxt/crux/pull/1472

[0] https://cs.stanford.edu/people/chrismre/papers/paper49.Ngo.p...