Karthik Divi
·3 min read

QuestDB Online Compiler and SQL Editor

onecompileronline-compilerdatabasequest-db

QuestDB is a time-series database built for speed. It uses a SQL interface, which makes it approachable if you already know SQL, but under the hood it is optimized for ingesting millions of rows per second. Think IoT sensor streams, financial tick data, server metrics -- anything where timestamps are the backbone of your queries.

Setting up QuestDB locally means pulling a Docker image or installing binaries, configuring ports, and making sure nothing conflicts. For a quick test or a learning session, that is overkill.

Running QuestDB queries in the browser

An online QuestDB editor gives you a ready-to-go environment. You open a tab, write your SQL, hit run, and see results. That is the whole workflow.

This is useful when you want to:

  • Try out time-series SQL syntax without installing anything
  • Test a SAMPLE BY or LATEST ON clause before putting it into production code
  • Share a query with a colleague who does not have QuestDB running locally
  • Practice for interviews that involve time-series data problems

QuestDB code example

Here is a typical QuestDB pattern -- creating a table with a designated timestamp and querying it with time bucketing:

CREATE TABLE sensor_readings (
  sensor_id SYMBOL,
  temperature DOUBLE,
  humidity DOUBLE,
  ts TIMESTAMP
) TIMESTAMP(ts) PARTITION BY DAY;

INSERT INTO sensor_readings VALUES
  ('sensor_a', 22.5, 45.0, '2025-01-15T10:00:00Z'),
  ('sensor_a', 23.1, 44.2, '2025-01-15T10:05:00Z'),
  ('sensor_a', 22.8, 46.1, '2025-01-15T10:10:00Z'),
  ('sensor_b', 19.3, 55.0, '2025-01-15T10:00:00Z'),
  ('sensor_b', 19.7, 54.8, '2025-01-15T10:05:00Z');

SELECT sensor_id, avg(temperature) AS avg_temp, avg(humidity) AS avg_hum, ts
FROM sensor_readings
SAMPLE BY 10m
ALIGN TO CALENDAR;

The SAMPLE BY keyword is QuestDB-specific. It groups rows into time buckets, which is something you would normally need window functions or subqueries for in other databases. This kind of syntax is worth experimenting with before you commit to using it in a pipeline.

Why an online editor beats a local setup for quick tests

QuestDB's fast ingestion and time-series extensions are its selling points, but you do not need a production cluster to learn them. An online SQL editor handles the small stuff well:

  • No Docker, no port configuration, no disk space concerns
  • The execution environment resets cleanly between runs
  • You can share a link to your query instead of pasting SQL into Slack
  • Works on any machine with a browser, including tablets when you are away from your desk

Try it on OneCompiler

OneCompiler has a QuestDB editor that supports the full SQL dialect, including time-series extensions. You write your query, run it, and get output in seconds.

Give it a shot here: QuestDB Online Compiler on OneCompiler

If you work with time-series data regularly, bookmarking this saves you from spinning up a local instance every time you need to verify a query.