Each Honeycomb Environment contains multiple Datasets, which group your data. Each Dataset represents a collection of related events that come from (or are related to) the same source. You can query within a single Dataset, or across the entire Environment.
Honeycomb uses two types of Datasets, each for different purposes:
Service Datasets: Datasets that contain events that represent distributed tracing spans.
Each service is distinguished by a service.name field or serviceName configuration.
A single trace can cross multiple different Service Datasets.
When you inspect a trace, Honeycomb’s query engine allows you to see the entire trace from any point by finding all spans across all the Services in the Environment that share the same trace id field.
General Datasets: Datasets that contain data that does not participate in traces, such as data from deployments, log sources, or metrics.
Each Dataset consists of schema, a set of data definitions, a set of custom fields, and a set of markers.
Manage your Honeycomb Datasets, which group your data into collections of related events. Learn how to create and delete Datasets, and how to change the Dataset description and set defaults.
Define your Dataset schema, including unique fields and custom fields. Otherwise known as Derived Columns, custom fields are computed properties that are calculated by a formula. Learn how to create, define, and delete custom fields.
Manage Honeycomb Markers at the Dataset level. Use markers to emphasize specific data points in time, such as deployments, incidents, activated or resolved triggers, and enabled or disabled feature flags. Learn how to create, delete, and change the appearance of markers.
