In Python, Node.js, the usual suspects. Even cooler would be a node.js/Gremlin bridge that gave you the graph object.
Query time, statistics, that sort of thing.
It's everywhere now, with subtly different semantics. Unify and do cool things (like abort).
Always good. Break out test_utils and compare text and Javascript outputs.
Also always good.
Usually something that should be taken care of.
Start discussing bootstrap triples, things that make the database self-describing, if they exist (though they need not). Talk about sameAs and indexing and type systems and whatnot.
It exists, it's indexed, but it's basically useless right now
There are some simple optimizations that can be done there. And was the first one to get right, this is the next one. A simple example is just to convert the HasA to a fixed (next them out) if the subiterator size is guessable and small.
A way to limit the number of subresults at a point, without even running the query. Essentially, much as GetLimit() does for the end, be able to do the same in between
Getting to the predicates from a node, or the nodes from a predicate, or some odd combinations thereof. Ditto for provenance.
Expose the value-comparison iterator in the language
See also bootstrapping. Things like finding "name" predicates, and various schema or type enforcement.
An important failure of MQL before was that it was never well-specified. Let's not fall in that trap again, and be able to document what everything means.
The necessary component to make mid-query limit work. Acts as a limit on Next(), a passthrough on Check(), and a limit on NextResult()
Because it's useful markup, and JSON is easy for Go to deal with. The NQuads library is nicely self-contained, there's no reason more formats can't be supported.
Since I have value comparison. It works, it's just not fast today. That could be improved.
Hopefully easy now that the AppEngine shim exists. Questionably fast.
It'd be nice to run on SQL as well. It's a big why not?
Notionally, this is a simple triple table with a number of indicies. Iterators and iterator optimization (ie, rewriting SQL queries) is the 'fun' part
This one is the crazy one. Suppose a world where we actually use the table schema for predicates, and update the table schema as we go along. Yes, it sucks when you add a new predicate (and the cell values are unclear) but for small worlds (or, "short schemas") it may (or may not) be interesting.
Really, this is just the generalized value comparison iterator, across strings and dates and such.
There's a whole body of work there, and a lot of interested researchers. They're the choir who already know the sermon of graph stores. Once ease-of-use gets people in the door, supporting extensions that make everyone happy seems like a win. And because we're query-language agnostic, it's a cleaner win. See also bootstrapping, which is the first goal toward this (eg, let's talk about sameAs, and index it appropriately.)
Technically it works now if you piggyback on someone else's replication, but that's cheating. We speak HTTP, we can send triple sets over the wire to some other instance. Bonus points for a way to apply morphisms first -- massive graph on the backend, important graph on the frontend.
Eg, topic service, recon service -- whether in Cayley itself or as part of the greater project.
Javascript is nice for first-timers but experienced graph folks may want something more. Experiment with new languages, including but not limited to things that feel a lot like Datalog.
Imagine an in-memory graph cache wrapped around another store.
This is the nutty one that's undefined and slow. The notion is to make graph-shapes more efficient, but it's unclear how that'll happen.
Can we access git in a meaningful fashion, giving a history and rollbacks to memory/flat files?