Hi all,

to move inventory forward, we need to port it to Tinkerpop3 - a new(ish) and
actively maintained version of the Tinkerpop graph API.

Apart from the huge improvement in the API expressiveness and capabilities,
the important thing is that it comes with a variety of backends, 2 of which
are of particular interest to us ATM. The Titan backend (with Titan in version
1.0) and SQL backend (using the sqlg library).

The SQL backend is a much improved (yet still unfinished in terms of
optimizations and some corner case features) version of the toy SQL backend
for Tinkerpop2.

Back in March I ran performance comparisons for SQL/postgres and Titan (0.5.4)
on Tinkerpop2 and concluded that Titan was the best choice then.

After completing a simplistic port of inventory to Tinkerpop3 (not taking
advantage of any new features or opportunities to simplify inventory
codebase), I've run the performance tests again for the 2 new backends - Titan
1.0 and Sqlg (on postgres).

This time the results are not so clear as the last time.
>From the charts [1] you can see that Postgres is actually quite a bit faster
on reads and can better handle concurrent read access while Titan shines in
writes (arguably thanks to Cassandra as its storage).

Of course, I can imagine that the read performance advantage of Postgres would
decrease with the growing amount of data stored (the tests ran with the
inventory size of ~10k entities) but I am quite positive we'd get competitive
read performance from both solutions up to the sizes of inventory we
anticipate (100k-1M entities).

Now the question is whether the insert performance is something we should be
worried about in Postgres too much. IMHO, there should be some room for
improvement in Sqlg and also our move to /sync for agent synchronization would
make this less of a problem (because there would be not that many initial
imports that would create vast amounts of entities).

Nevertheless I currently cannot say who is the "winner" here. Each backend has
its pros and cons:

Titan:
Pros:
- high write throughput
- backed by cassandra

Cons:
- slower reads
- project virtually dead
- complex codebase (self-made fixes unlikely)

Sqlg:
Pros:
- small codebase
- everybody knows SQL
- faster reads
- faster concurrent reads

Cons:
- slow writes
- another backend needed (Postgres)

Therefore my intention here is to go forward with a "proper" port to
Tinkerpop3 with Titan still enabled but focus primarily on Sqlg to see if we
can do anything with the write performance.

IMHO, any choice we make is "workable" as it is even today but we need to
weigh in the productization requirements. For those Sqlg with its small dep
footprint and postgres backend seems preferable to the huge dependency mess of
Titan.

[1] https://dashboards.ly/ua-TtqrpCXcQ3fnjezP5phKhc

--
Lukas Krejci
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