questdb-quickstart

QuestDB is an Apache 2.0 licensed time-series database for high throughput ingestion and fast SQL queries with operational simplicity. To learn more about QuestDB visit https://questdb.io

This is a quickstart covering:

• Getting started with QuestDB on docker
• Loading data using a CSV
• Using the web console for interactive queries
• Ingesting real-time data using the official clients in Go, Java, or Python
• Real-time dashboards with Grafana and QuestDB using the PostgreSQL connector

For a video walkthrough, please visit:

Deploying the demo

This quickstart requires starting or deploying QuestDB, Grafana, and some ingestion scripts. You have three ways of setting this up:

• Fully managed cloud-based installation (requires creating a free account on gitpod) using the Gitpod link in the next section. Recommended for quick low-friction demo
• Local installation using docker-compose. Recommended for quick low-friction demo, as long as you have docker/docker-compose installed locally and are comfortable using them
• Local installation using docker but doing step-by-step. Recommended to learn more about the details and how everything fits together

After you install with your preferred method (instructions below) you can proceed to loading and querying data

Fully managed deployment using Gitpod

When you click the button below, gitpod will provision an environment with questdb, a python script generating demo data, and a grafana dashboard for visualisation. On finishing (typically about one minute), gitpod will try to open two new tabs, one with the grafana dashboard, one with the QuestDB web interface. When opening the grafana dashboard, user is "demo" and password is "quest".

Click the button below to start a new development environment:

Note: If you already have a gitpod account, you will need to log in when launching the deployment. If you don't have a gitpod account, you can create one for free when launching the deployment. If your browser is blocking pop-ups, you will need to click on the alert icon on the navigation bar to open the two links after the deployment is complete.

If you want to explore loading batch data using the web interface or the REST API, please visit loading and querying data. Note you will need to use the endpoint provided by gitpod, rather than the default http://localhost:9000.

Docker-compose local deployment

Docker compose will provision an environment with questdb, a python script generating demo data, and a grafana dashboard for visualisation. The whole process will take about 2-3 minutes, depending on yout internet speed downloading the container images, and how quick your machine can build a python-based docker image.

git clone https://github.com/questdb/questdb-quickstart.git
cd questdb-quickstart
docker-compose up

The grafana web interface will be available at http://localhost:3000/d/qdb-ilp-demo/device-data-questdb-demo?orgId=1&refresh=5s. User is "demo" and password is "quest".

The QuestDB console is available at http://localhost:9000

If you want to explore loading batch data using the web interface or the REST API, please visit loading and querying data.

Stop the demo via:

docker-compose down

Local docker based deployment

The local deployment has four steps: starting QuestDB, loading batch data, ingesting real-time data, and creating dashboards with Grafana.

Starting QuestDB

There are many ways to install QuestDB, but I am choosing docker for portability. Note I won't be using a docker volume and the data will be ephemeral. Check the QuestDB docks to see how to start with a persistent directory.

docker run --add-host=host.docker.internal:host-gateway -p 9000:9000 -p 9009:9009 -p 8812:8812 -p 9003:9003 questdb/questdb:latest

Port 9000 serves the web console, port 9009 is for streaming ingestion, port 8812 is for PostgreSQL-protocol reads or writes, port 9003 is a monitoring/metrics endpoint.

Importing batch data

If you want to explore loading batch data using the web interface or the REST API, please visit loading and querying data. If you are only interested in streaming data you can skip this step.

Ingesting real-time data using the official clients in Go, Java, or Python

We will generate simulated IoT data and will use the QuestDB client libraries to ingest in real-time into questdb. Depending on your language of choice, follow the instructions at

• https://github.com/javier/questdb-quickstart/tree/main/ingestion/go
• https://github.com/javier/questdb-quickstart/tree/main/ingestion/java
• https://github.com/javier/questdb-quickstart/tree/main/ingestion/python

Real-time dashboards with Grafana and QuestDB using the PostgreSQL connector

Please follow the instructions at https://github.com/javier/questdb-quickstart/tree/main/dashboard/grafana