Prometheus Query Language

GreptimeDB can be used as a drop-in replacement for Prometheus in Grafana, because GreptimeDB supports PromQL (Prometheus Query Language). GreptimeDB has reimplemented PromQL natively in Rust and exposes the ability to several interfaces, including the HTTP API of Prometheus, the HTTP API of GreptimeDB, and the SQL interface.

Prometheus' HTTP API

GreptimeDB has implemented a set of Prometheus compatible APIs under HTTP context /v1/prometheus/:

• Instant queries /api/v1/query
• Range queries /api/v1/query_range
• Series /api/v1/series
• Label names /api/v1/labels
• Label values /api/v1/label/<label_name>/values

It shares same input and output format with original Prometheus HTTP API. You can also use GreptimeDB as an in-place replacement of Prometheus. For example in Grafana Prometheus data source, set http://localhost:4000/v1/prometheus/ as context root of Prometheus URL.

Consult Prometheus documents for usage of these API.

You can use additional query parameter db to specify GreptimeDB database name.

For example, the following query will return the CPU usage of the process_cpu_seconds_total metric in the public database:

curl -X POST \
    -H 'Authorization: Basic {{authorization if exists}}' \
    --data-urlencode 'query=irate(process_cpu_seconds_total[1h])' \
    --data-urlencode 'start=2024-11-24T00:00:00Z' \
    --data-urlencode 'end=2024-11-25T00:00:00Z' \
    --data-urlencode 'step=1h' \
    --data-urlencode 'db=public' \
    http://localhost:4000/v1/prometheus/api/v1/query_range

If authentication is enabled in GreptimeDB, the authentication header is required. Refer to the authentication documentation for more details.

The query string parameters for the API are identical to those of the original Prometheus API, with the exception of the additional db parameter, which specifies the GreptimeDB database name.

The output format is compatible with the Prometheus API:

{
  "status": "success",
  "data": {
    "resultType": "matrix",
    "result": [
      {
        "metric": {
          "job": "node",
          "instance": "node_exporter:9100",
          "__name__": "process_cpu_seconds_total"
        },
        "values": [
          [
            1732618800,
            "0.0022222222222222734"
          ],
          [
            1732622400,
            "0.0009999999999999788"
          ],
          [
            1732626000,
            "0.0029999999999997585"
          ],
          [
            1732629600,
            "0.002222222222222175"
          ]
        ]
      }
    ]
  }
}

SQL

GreptimeDB also extends SQL grammar to support PromQL. You can start with the TQL (Time-series Query Language) keyword to write parameters and queries. The grammar looks like this:

TQL [EVAL|EVALUATE] (<START>, <END>, <STEP>) <QUERY>

<START> specifies the query start range and <END> specifies the end time. <STEP> identifies the query resolution step width. All of them can either be an unquoted number (represent UNIX timestamp for <START> and <END>, and duration in seconds for <STEP>), or a quoted string (represent an RFC3339 timestamp for <START> and <END>, and duration in string format for <STEP>).

For example:

TQL EVAL (1676738180, 1676738780, '10s') sum(some_metric)

You can write the above command in all places that support SQL, including the GreptimeDB HTTP API, SDK, PostgreSQL and MySQL client etc.

Multiple fields

Based on the table model, GreptimeDB supports multiple fields in a single table(or metric, in the context of Prometheus). Queries will run on every fields by default. Or you can use the special filter __field__ to query a specific field(s):

metric{__field__="field1"}

Exclude or regex are also supported:

metric{__field__!="field1"}

metric{__field__=~"field_1|field_2"}

metric{__field__!~"field_1|field_2"}

Limitations

Though GreptimeDB supports a rich set of data types, the PromQL implementation is still limited to the following types:

• timestamp: Timestamp
• tag: String
• value: Double

Currently only a subset of PromQL is supported. Here attaches the compatibility list. You can also check our latest compliance report in this tracking issue.

Literal

Both string and float literals are supported, with the same rule as PromQL.

Selector

Both instant and range selector are supported. The only exception is the label matching on metric name, e.g.: {__name__!="request_count}" (but the equal-matching case is supported: {__name__="request_count}").

Time duration and offset are supported, but @ modifier is not supported yet.

Timestamp precision

The timestamp precision in PromQL is limited by its query syntax, only supporting calculations up to millisecond precision. However, GreptimeDB supports storing high-precision timestamps, such as microseconds and nanoseconds. When using PromQL for calculations, these high-precision timestamps are implicitly converted to millisecond precision.

Binary

Pure literal binary-expr like 1+1 is not supported yet.

• Supported:

  Operator	Example
  add	a + b
  sub	a - b
  mul	a * b
  div	a / b
  mod	a % b
  eqlc	a == b
  neq	a != b
  gtr	a > b
  lss	a < b
  gte	a >= b
  lte	a <= b

• Unsupported:

  Operator	Progress
  power	TBD
  atan2	TBD
  and	TBD
  or	TBD
  unless	TBD

Aggregators

• Supported:

  Aggregator	Example
  sum	sum by (foo)(metric)
  avg	avg by (foo)(metric)
  min	min by (foo)(metric)
  max	max by (foo)(metric)
  stddev	stddev by (foo)(metric)
  stdvar	stdvar by (foo)(metric)

• Unsupported:

  Aggregator	Progress
  count	TBD
  grouping	TBD
  topk	TBD
  bottomk	TBD
  count_values	TBD

Instant Functions

• Supported:

  Function	Example
  abs	abs(metric)
  ceil	ceil(metric)
  exp	exp(metric)
  ln	ln(metric)
  log2	log2(metric)
  log10	log10(metric)
  sqrt	sqrt(metric)
  acos	acos(metric)
  asin	asin(metric)
  atan	atan(metric)
  sin	sin(metric)
  cos	cos(metric)
  tan	tan(metric)
  acosh	acosh(metric)
  asinh	asinh(metric)
  atanh	atanh(metric)
  sinh	sinh(metric)
  cosh	cosh(metric)
  scalar	scalar(metric)
  tanh	tanh(metric)
  timestamp	timestamp()
  histogram_quantile	histogram_quantile(phi, metric)

• Unsupported:

  Function	Progress / Example
  absent	TBD
  sgn	TBD
  sort	TBD
  sort_desc	TBD
  deg	TBD
  rad	TBD
  other multiple input fns	TBD

Range Functions

• Supported:

  Function	Example
  idelta	idelta(metric[5m])
  <aggr>_over_time	count_over_time(metric[5m])
  stddev_over_time	stddev_over_time(metric[5m])
  stdvar_over_time	stdvar_over_time(metric[5m])
  changes	changes(metric[5m])
  delta	delta(metric[5m])
  rate	rate(metric[5m])
  deriv	deriv(metric[5m])
  increase	increase(metric[5m])
  irate	irate(metric[5m])
  reset	reset(metric[5m])