QuestDB 6.0.4 July release, Prometheus metrics support

We've published the latest QuestDB release, and it focuses on community-driven topics raised with us recently by our users. The features included are performance improvements, increased parallelization of existing code, and calendar alignment for SAMPLE BY queries. Also included is the introduction of a framework for exposing Prometheus metrics by our community member Piotr Rżysko. Here's the full roundup of changes that have just landed!

QuestDB 6.0.4

This release fixes issues raised and prioritized by the developer community, and includes stability fixes across several subsystems. The addition of a framework for Prometheus metrics is an exciting feature that we expect will be continuously developed with more types of counters and gauges added as we get feedback on its use. The addition of monitoring using Prometheus will simplify how users gain insights into the performance and activity of deployed instances of QuestDB.

SAMPLE BY with calendar alignment

It's now possible to perform SAMPLE BY queries where the sampled groups align strictly to calendar dates with optional time zones and offsets. The default behavior for sampling is unchanged from previous releases, and calendar alignment is possible through the use of the following optional keywords:

SELECT ts, count() FROM sensors
-- additional configuration for offsets and time zones

For more information on using calendar alignment with sampled groups, see the SAMPLE BY documentation.

SQL performance improvements

We gathered user feedback on the most critical query types that require faster execution speed, and we have improved LATEST BY handling internally. These enhancements are possible by massively parallelizing how these operations are executed and optimizing aggregate calculations within sampled groups. Users will see these improvements with the following two query types:

-- indexed columns
SELECT * FROM my_table LATEST BY indexed_col;
-- indexed columns with filtering using WHERE
SELECT * FROM my_table LATEST BY indexed_col WHERE other_col > 9000;

Prometheus metrics

The new implementation for Prometheus monitoring allows for adding basic counters and will be improved in upcoming releases. To activate Prometheus metrics, set the metrics.enabled key to true in QuestDB's server.conf configuration file:


Create a Prometheus configuration file that points to QuestDB's metrics endpoint on 9003:

scrape_interval: 15s
monitor: "questdb"

- job_name: "questdb"
scrape_interval: 5s
- targets: [""]

Start Prometheus, passing the configuration file with the QuestDB settings:

prometheus --config.file=questdb.yml
Prometheus monitoring server metrics from a QuestDB instance
Basic counter for number of SQL queries executed

The initial implementation adds a basic counter for the number of executed SQL queries which can be charted, or alerts may be configured for this metric. If you have some suggestions for the types of counters and gauges we should include, let us know on GitHub.

Breaking changes

The addition of special handling for null in #1179 introduces changes that enforce timestamps having only positive values. This means that timestamps cannot predate epoch 0 in UTC, disallowing pre-1970 values.

How to run QuestDB 6.0.4

The release notes including a changelog is available on GitHub and this version has been published to Docker Hub:

docker pull questdb/questdb:6.0.4

To start up QuestDB, use docker run:

docker run -p 9000:9000 -p 8812:8812 -p 9009:9009 \

Next up

We are now trying out GitHub discussions as a way to get the conversation about QuestDB started! We have some great topics already so far since we activated this feature, and we expect this to be a fun and easy way to get involved on GitHub with open-ended discussions.

We're eagerly awaiting feedback on this release, so feel free to reach out and tell us how this version is running. Let us know how we're doing or just come by and say hello in our Slack Community or browse the repository on GitHub.

Download QuestDB Open source under Apache 2.0. Blazing fast ingest. SQL analytics.