Just as with PostgreSQL and MongoDB, frequently having an index becomes very important to query performance for your "hot paths" for your database querying habits.
Let's say a new facet of our app is that people can find celebrities born the same year they are. Your query would look something like this.
MATCH (p:Person) WHERE p.born = 1967 RETURN p;
A fairly simple query but like we've seen before, this will look at every person on the graph to examine their birth year. Imagine you had all of IMDB's database; that query could wreck a system. Let's use EXPLAIN to see why.
EXPLAIN MATCH (p:Person) WHERE p.born = 1967 RETURN p;
You'll see it gives you a pretty in-depth answer that it will scan all 133 persons and then narrow it down to 13. Let's throw an index on Person's born attribute.
CREATE INDEX FOR (p:Person) ON (p.born);
EXPLAIN MATCH (p:Person) WHERE p.born = 1967 RETURN p;
MATCH (p:Person) WHERE p.born = 1967 RETURN p;
You should see the index being used. With only 133 nodes it'd be hard to perceive a performance increase but on a large list it would likely be significant.
Neo4j has a great article on query planning if you want to dig further into improving query performance.
Lastly, sometimes it's useful to see all existing indexes. Try this:
SHOW INDEXES;
