Vector

Vector is a high-performance observability data pipeline that puts organizations in control of their observability data. Our integration page on Vector is here.

Integration

GreptimeDB can be used as a Vector Sink component to receive metrics. To integrate Vector with GreptimeDB, use the following configuration:

[sinks.my_sink_id]
inputs = ["my-source-or-transform-id"]
type = "greptimedb"
endpoint = "<host>:4001"
dbname = "<dbname>"
username = "<username>"
password = "<password>"

For more configuration options, see Vector GreptimeDB Configuration.

GreptimeDB uses gRPC to communicate with Vector, so the default port for the Vector sink is 4001. If you have changed the default gRPC port when starting GreptimeDB with custom configurations, use your own port instead.

Data Model

The following rules are used when storing Vector metrics into GreptimeDB:

• Use <metric namespace>_<metric name> as the table name in GreptimeDB, for example, host_cpu_seconds_total;
• Use the timestamp of the metric as the time index of GreptimeDB, the column name is ts;
• Use the tags of the metric as GreptimeDB tags;
• For Vector metrics which have multiple subtypes:
  • For Counter and Gauge metrics, the values are stored in the val column;
  • For Set metrics, the number of data points are stored in the val column;
  • For Distribution metrics, the values of each percentile are stored in the pxx column, where xx is the percentile, and the min/max/avg/sum/count columns are also stored;
  • For AggregatedHistogram metrics, the values of each bucket are stored in the bxx column, where xx is the upper limit of the bucket, and the sum/count columns are also stored;
  • For AggregatedSummary metrics, the values of each percentile are stored in the pxx column, where xx is the percentile, and the sum/count columns are also stored;
  • For Sketch metrics, the values of each percentile are stored in the pxx column, where xx is the percentile, and the min/max/avg/sum columns are also stored;