cayley

This is what we are trying to do with Cayley https://github.com/cayleygraph/cayley

So one thing I still don't understand is whether Neo4J a pure graph database is better than using something like AegensGraph[0] or Cayley[1], which uses a pre-existing DB engine for their persistent layer. If yes, what are the advantages? Is it something that totally depends on the use case? If it is, what criteria should be used to make a decision? [0]:https://github.com/bitnine-oss/agensgraph [1]:https://github.com/cayleygraph/cayley

Adding Cayley to the mix: https://github.com/cayleygraph/cayley

http://janusgraph.org/ Support for various storage backends: - Apache Cassandra® - Apache HBase® - Google Cloud Bigtable - Oracle BerkeleyDB I don't understand how a database doesn't have its own native store. What exactly does a graph database actually do if it doesn't manage the data fed to it? Same is true for CayleyGraph† https://github.com/cayleygraph/cayley and proabably others. †Plays well with multiple backend stores: - KVs: Bolt, LevelDB - NoSQL: MongoDB - SQL: PostgreSQL, CockroachDB, MySQL - In-memory, ephemeral

+1 Insightful. In fact, there's research toward showing the two are equivalent in possibility space of what can be represented/queried (https://arxiv.org/abs/1102.1889) But yes, linked data and graphs are super powerful once the data is triplified. Suddenly you have an abstraction above the contents of your data into the 'shape' of your data. SPARQL and RDF aren't going away, but they're the academic thing that I and others are trying to make useful. GraphQL is scratching the surface, but it's super exciting that it's scratching at all, imo. (Disclosure: Founded CayleyGraph, supporting the open source https://github.com/cayleygraph/cayley, which I maintain and mostly wrote)

I'm flattered. If you like the Torus style, https://github.com/coreos/go-tcmu is a package I'm quite proud of (SCSI interactions wrapped in a nice pure-Go interface) and then a plug for https://github.com/cayleygraph/cayley which is a little rougher but a nice community and large codebase I maintain. Bolt (also here mentioned) is one of my favorite beautiful codebases. https://github.com/mdlayher is a prolific author with lots of good protocol implementations. https://github.com/chihaya/chihaya is a fun project if you're into BitTorrent.

There is also Cayley (https://github.com/cayleygraph/cayley) which supports more query languages, including GraphQL, and multiple backend stores.

Cayley's graph data layout is most similar to a Hexastore-style [1] triple store, though IIRC it doesn't do the full six-way index that the original Hexastore paper describes. The Redis page on secondary indexing [2] has a great quick intro to what this actually entails (search the page for Hexastore). As you might guess from the Redis link, this style of graph lends itself well to KV stores, so the answer to your question #1 might be that it's a long-term decision, but the style of graph is really designed for a KV store anyway. But I haven't discussed this at all with the Cayley devs so I can't actually speak for them. I'm using it with the BoltDB backend and have been pleased with the performance overall. I haven't looked at the backends for more complex databases like Postgres in detail, but it does appear that the backend interface h

Yeah, we're still getting the marketing site up, complete with docs. Til then, there's https://github.com/cayleygraph/cayley/tree/master/docs with the content

https://github.com/cayleygraph/cayley is currently on the frontpage of HN, and it does use PGSQL as backend.

Say, you were an early contributor to Cayley! (https://github.com/cayleygraph/cayley) Things were slow there for a while, but we have our own namespace now, we've done about a release per quarter for a bit, and have a small but thriving community on our discussion board: https://discourse.cayley.io Currently up for discussion is reification :)

this project https://github.com/google/cayley seems to have gone the route of using pluggable backends.