Cayley is an open-source graph inspired by the graph database behind [Freebase](http://freebase.com) and Google's [Knowledge Graph](https://en.wikipedia.org/wiki/Knowledge_Graph). Its goal is to be a part of the developer's toolbox where [Linked Data](http://linkeddata.org/) and graph-shaped data (semantic webs, social networks, etc) in general are concerned. [](https://travis-ci.org/google/cayley) [Trello Board](https://trello.com/b/KioFZb5O) ## Features * Written in [Go](http://golang.org) * Easy to get running (3 or 4 commands, below) * RESTful API * or a REPL if you prefer * Built-in query editor and visualizer * Multiple query languages: * JavaScript, with a [Gremlin](http://gremlindocs.com/)-inspired\* graph object. * (simplified) [MQL](https://developers.google.com/freebase/v1/mql-overview), for Freebase fans * Plays well with multiple backend stores: * [LevelDB](https://github.com/google/leveldb) * [Bolt](https://github.com/boltdb/bolt) * [MongoDB](https://www.mongodb.org) for distributed stores * In-memory, ephemeral * Modular design; easy to extend with new languages and backends * Good test coverage * Speed, where possible. Rough performance testing shows that, on consumer hardware and an average disk, 134m quads in LevelDB is no problem and a multi-hop intersection query -- films starring X and Y -- takes ~150ms. \* Note that while it's not exactly Gremlin, it certainly takes inspiration from that API. For this flavor, [see the documentation](docs/GremlinAPI.md). ## Getting Started Grab the latest [release binary](https://github.com/google/cayley/releases) and extract it wherever you like. If you prefer to build from source, see the documentation on the wiki at [How to start hacking on Cayley](https://github.com/google/cayley/wiki/How-to-start-hacking-on-Cayley) or type ``` mkdir -p ~/cayley && cd ~/cayley export GOPATH=`pwd` export PATH=$PATH:~/cayley/bin mkdir -p bin pkg src/github.com/google cd src/github.com/google git clone https://github.com/google/cayley cd cayley go get github.com/tools/godep godep restore go build ./cmd/cayley ``` Then `cd` to the directory and give it a quick test with: ``` ./cayley repl --dbpath=data/testdata.nq ``` To run the web frontend, replace the "repl" command with "http" ``` ./cayley http --dbpath=data/testdata.nq ``` You should see a `cayley>` REPL prompt. Go ahead and give it a try: ``` // Simple math cayley> 2 + 2 // JavaScript syntax cayley> x = 2 * 8 cayley> x // See all the entities in this small follow graph. cayley> graph.Vertex().All() // See only dani. cayley> graph.Vertex("dani").All() // See who dani follows. cayley> graph.Vertex("dani").Out("follows").All() ``` **Running the visualizer on the web frontend** To run the visualizer: click on visualize and enter: ``` // Visualize who dani follows. g.V("dani").Tag("source").Out("follows").Tag("target").All() ``` The visualizer expects to tag nodes as either "source" or "target." Your source is represented as a blue node. While your target is represented as an orange node. The idea being that our node relationship goes from blue to orange (source to target). **Sample Data** For somewhat more interesting data, a sample of 30k movies from Freebase comes in the checkout. ``` ./cayley repl --dbpath=data/30kmoviedata.nq.gz ``` To run the web frontend, replace the "repl" command with "http" ``` ./cayley http --dbpath=data/30kmoviedata.nq.gz ``` And visit port 64210 on your machine, commonly [http://localhost:64210](http://localhost:64210) ## Running queries The default environment is based on [Gremlin](http://gremlindocs.com/) and is simply a JavaScript environment. If you can write jQuery, you can query a graph. You'll notice we have a special object, `graph` or `g`, which is how you can interact with the graph. The simplest query is merely to return a single vertex. Using the 30kmoviedata.nq dataset from above, let's walk through some simple queries: ```javascript // Query all vertices in the graph, limit to the first 5 vertices found. graph.Vertex().GetLimit(5) // Start with only one vertex, the literal name "Humphrey Bogart", and retrieve all of them. graph.Vertex("Humphrey Bogart").All() // `g` and `V` are synonyms for `graph` and `Vertex` respectively, as they are quite common. g.V("Humphrey Bogart").All() // "Humphrey Bogart" is a name, but not an entity. Let's find the entities with this name in our dataset. // Follow links that are pointing In to our "Humphrey Bogart" node with the predicate "name". g.V("Humphrey Bogart").In("name").All() // Notice that "name" is a generic predicate in our dataset. // Starting with a movie gives a similar effect. g.V("Casablanca").In("name").All() // Relatedly, we can ask the reverse; all ids with the name "Casablanca" g.V().Has("name", "Casablanca").All() ``` You may start to notice a pattern here: with Gremlin, the query lines tend to: Start somewhere in the graph | Follow a path | Run the query with "All" or "GetLimit" g.V("Casablanca") | .In("name") | .All() And these pipelines continue... ```javascript // Let's get the list of actors in the film g.V().Has("name","Casablanca") .Out("/film/film/starring").Out("/film/performance/actor") .Out("name").All() // But this is starting to get long. Let's use a morphism -- a pre-defined path stored in a variable -- as our linkage var filmToActor = g.Morphism().Out("/film/film/starring").Out("/film/performance/actor") g.V().Has("name", "Casablanca").Follow(filmToActor).Out("name").All() ``` There's more in the JavaScript API Documentation, but that should give you a feel for how to walk around the graph. ## Disclaimer Not a Google project, but created and maintained [by a Googler](https://github.com/barakmich), with permission from and assignment to Google, under the [Apache License, version 2.0](http://www.apache.org/licenses/LICENSE-2.0). ## Contact * Email list: [cayley-users at Google Groups](https://groups.google.com/forum/?hl=en#!forum/cayley-users) * Twitter: [@cayleygraph](https://twitter.com/cayleygraph) * IRC: [#cayley on Freenode](http://webchat.freenode.net/?channels=%23cayley&uio=d4)