Everything on this page runs on the Florida road network of the 9th DIMACS Implementation Challenge: 1,070,376 junctions with their coordinates and 2,712,798 road segments with a length (km) and a travel time (minutes). The route-planning use case downloads it and loads it with one request to the GraphBatch endpoint, in about 11 seconds. With Docker:

git clone https://github.com/ArcadeData/arcadedb-usecases.git
cd arcadedb-usecases/route-planning
docker compose up -d     # starts ArcadeDB on port 2480
./setup.sh               # downloads Florida, loads it, creates the view with CCH (km, minutes)
./queries/queries.sh     # every query of this page, through curl

The java folder runs the same queries from a Java client, and embedded/FloridaRoutes.java runs them in an embedded database with no server and no build step: it loads the network with the GraphBatch Java API, compares dijkstra(), astar() and cchShortestPath() on the same route, shows the two costs, and applies the traffic jam.

java -Xmx4g -cp "$ARCADEDB_HOME/lib/*" embedded/FloridaRoutes.java

Through the HTTP API, Tallahassee to Coral Gables takes about 3 seconds with dijkstra(), 6 seconds with astar() and 2 milliseconds with cchShortestPath(). The SQL functions walk the stored records, while the hierarchy reads the in-memory view; the benchmark above compares all three on that same view. The Shortest Path guide covers every option, from the unweighted shortestPath() to A* heuristics, and how to check which engine answered a query.