1. A method for processing data at data intake for detection of an anomaly in a distributed computer environment, the method comprising: receiving event data representing an event on a computer network, the event data being indicative of a plurality of entities and an action involved in the event; identifying the entities and a relationship between the entities, based on the action in the event data; creating, for the event, a record of the relationship between the entities by using a data structure representing a relationship graph, the relationship graph including at least two nodes and an edge between the two nodes, each node representing one of the entities, the edge representing the relationship between the entities; and creating an updated event data by appending the event data representing the event with the record of the relationship; wherein the record of the relationship is specific to the event; sending the updated event data to an event processing engine for further processing; generating a composite relationship graph that is combined from a plurality of the relationship graph corresponding to a plurality of the updated event data; and using the event processing engine to perform analytics on the plurality of the updated event data and the composite relationship graph; wherein the anomaly detection is performed based on applying a machine learning model to perform analytics on at least a portion of the composite relationship graph.