[Firebase data model](https://firebase.google.com/docs/firestore/data-model) is a hierarchy of documents that can contain (sub)-collections. This structure can be multiple levels deep; documents and subcollections are alternating in this hierarchy.

We use the following structure to store feature data in the Firestore:

* at the first level, there is a collection for each Feast project

* second level, in each project-collection, there is a Firebase document for each Feature Table

* third level, in the document for the Feature Table, there is a subcollection called `values` that contain a document per feature row. That document contains the following fields:

* `key` contains entity key as serialized `feast.types.EntityKey` proto

* `value` contains value as serialized `feast.types.Value` proto

* `event_ts` contains event timestamp (in the native firestore timestamp format)

* `created_ts` contains write timestamp (in the native firestore timestamp format)

Document id for the feature document is computed by hashing entity key using murmurhash3_128 algorithm as follows:

1. hash utf8-encoded entity names, sorted in alphanumeric order

2. hash the entity values in the same order as corresponding entity names, by serializing them to bytes as follows:

- binary values are hashed as-is

- string values hashed after serializing them as utf8 string

- int64 and int32 hashed as little-endian byte representation (8 and 4 bytes respectively)

- bool hashed as 0 or 1 byte

Other types of entity keys are not supported in this version of the specification, when using Cloud Firestore.

**Example:**


syntax = "proto3";

import "feast/types/Value.proto";

package feast.types;

option java_package = "feast.proto.types";

option java_outer_classname = "EntityKeyProto";

option go_package = "github.com/feast-dev/feast/sdk/go/protos/feast/types";

message EntityKey {

repeated string entity_names = 1;

repeated feast.types.Value entity_values = 2;

}