crux VS mergestat-lite

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...

You can query git with this: https://github.com/mergestat/mergestat if you like the idea.

Hey, author here, happy to answer any questions! Also checkout this notebook for a deeper dive into sqlite-lines, along with a slick WASM demonstration and more thoughts on the codebase itself https://observablehq.com/@asg017/introducing-sqlite-lines

I really dig SQLite, and I believe SQLite extensions will push it to another level. I rarely reach for Pandas or other "traditional" tools and query languages, and instead opt for plain ol' SQLite and other extensions. As a shameless plug, I recently started a blog series on SQLite and related tools and extensions if you want to learn more! Next week I'll be publishing more SQLite extensions for parsing HTML + making HTTP requests https://observablehq.com/@asg017/a-new-sqlite-blog-series

A few other SQLite extensions:

- xlite, for reading Excel files, in Rust https://github.com/x2bool/xlite

- sqlean, several small SQLite extensions in C https://github.com/nalgeon/sqlean

- mergestat, several SQLite extensions for developers (mainly Github's API) in Go https://github.com/mergestat/mergestat

mergestat is an open-source tool that allows users to run SQL queries on the contents and history of git repositories.

Thanks for this write up! I've been really interested in postgres compatibility in the context of a tool I maintain (https://github.com/mergestat/mergestat) that uses SQLite. I've been looking for a way to expose the SQLite capabilities over a more commonly used wire-protocol like postgres (or mysql) so that existing BI and visualization tools can access the data.

This project is an interesting one: https://github.com/dolthub/go-mysql-server that provides a MySQL interface (wire and SQL) to arbitrary "backends" implemented in go.

It's really interesting how compatibility with existing protocols has become an important feature of new databases - there's so much existing tooling that already speaks postgres (or mysql), being able to leverage that is a huge advantage IMO

timediff is a Go package for printing human readable, relative time differences. Output is based on ranges defined in the Day.js JavaScript library, and can be customized if needed. It's currently used by the mergestat command-line interface.

Assuming committers adhere to it, there could be some interesting use cases when combined with a tool like AskGit (https://github.com/askgitdev/askgit) for understanding what "categories" of work is being done in a codebase.

Maybe even what directories/files tend to see `fix` or `refactor` more frequently (signs of a poorly design or "hot" area?)

I've been very curious to explore this type of use case with askgit (https://github.com/augmentable-dev/askgit) which was designed for running simple "slice and dice" queries and aggregations on git history (and change stats) for basic analytical purposes. I've been curious about how this could be applied to a small text+git based "db". Say, for a regular json or CSV dumps.

This also reminds me of Dolt: https://github.com/dolthub/dolt which I believe has been on HN a couple times