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Online SQL compiler for running queries in your browser

An online SQL compiler lets you run SQL queries directly in your browser without setting up a local database. You can create tables, insert sample data, and use the environment as an SQL sandbox for testing query ideas.

Updated · SQL Arena team

SQL sandboxAll problems

What you will practice

  • Create tables and sample datasets
  • Run SQL directly in the browser
  • Test JOINs and aggregations on custom data
  • Compare behavior across SQL dialects
  • Move from free-form experiments to checked exercises

A practice problem in the trainer

This is how a problem looks in SQL Arena: the task, the editor, the result and the database schema.

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Test an aggregate query in an online SQL editor

You have campaigns and their related conversions. Return each campaign name as name, the number of conversions as conversions_count, and total revenue as total_revenue. Sort by revenue descending, then by campaign name when totals are equal.

Query 1PostgreSQLv16
SELECT
  c.name,
  COUNT(cv.id) AS conversions_count,
  SUM(cv.revenue) AS total_revenue
FROM campaigns c
JOIN conversions cv ON cv.campaign_id = c.id
GROUP BY c.id, c.name
ORDER BY total_revenue DESC, c.name;
Submit
Resultcampaignsconversions
Answer accepted

How to use an online SQL compiler: worked example

A sandbox is most useful when you control both the schema and the data. Here, campaigns contains one row per marketing campaign and uses id as its primary key. conversions stores individual conversion events, with campaign_id pointing back to campaigns.id. That small schema is enough to test several common SQL operations together: JOIN, COUNT, SUM, GROUP BY, and ORDER BY.

The JOIN matches each conversion with its parent campaign through cv.campaign_id = c.id. A campaign with several conversions therefore appears several times in the joined row set. COUNT(cv.id) measures how many conversion rows belong to each campaign, while SUM(cv.revenue) adds their revenue. GROUP BY c.id, c.name collapses those joined rows into one result row per campaign. Including the id keeps the grouping tied to the actual campaign record rather than assuming names are unique forever.

The final ORDER BY sorts campaigns by total revenue from highest to lowest. Autumn Search and Winter Search both total 200, so c.name is added as a second sort key. That makes the output deterministic. In an online SQL editor, you can now change one value, insert another conversion, replace the JOIN, or rewrite the aggregation and immediately see how the result changes.

An online SQL query compiler is useful when you want to test a query without installing and configuring a database locally. A typical SQL sandbox lets you define tables, insert sample rows, and then experiment with SELECT, JOIN, GROUP BY, and other statements. It can also work as a lightweight SQL editor for practice. Keep the SQL dialect in mind: PostgreSQL, MySQL, ClickHouse, and BigQuery share many concepts, but functions, data types, and some syntax differ.

SQLPostgreSQL v16
SELECT
  c.name,
  COUNT(cv.id) AS conversions_count,
  SUM(cv.revenue) AS total_revenue
FROM campaigns c
JOIN conversions cv ON cv.campaign_id = c.id
GROUP BY c.id, c.name
ORDER BY total_revenue DESC, c.name;
Query result
nameconversions_counttotal_revenue
Creator Week3320
Autumn Search2200
Winter Search1200
Product Digest1110
Partner Launch2100

Common mistakes when using an SQL sandbox

01

Joining without the correct relationship

If campaign_id is not matched to campaigns.id correctly, the query can produce far more rows than expected. Aggregates such as COUNT and SUM will then be inflated because conversions are attached to the wrong campaigns.

02

Forgetting that a JOIN changes row granularity

After the JOIN, one campaign row can become several rows because it has several conversions. COUNT(*) at that stage counts joined rows, not campaigns, so it is important to know what one row represents before aggregating.

03

Using an incomplete ORDER BY

Sorting only by total_revenue leaves ties without a guaranteed order. Adding campaign name as a second key makes the result stable and easier to verify while experimenting.

Practice problems on this topic

SQL sandbox

An online SQL sandbox is for free-form testing: you provide the schema, data, and query. A practice engine serves a different purpose. It gives you a defined problem and checks your answer against a reference result on hidden data, so a query must work beyond the sample you can see. After experimenting in the sandbox, you can move into exercises such as comparing platform conversion, finding platforms with successful payments, or aggregating paid events by city. SQL Arena contains 1,192 tasks. The free plan includes 292 tasks across PostgreSQL, MySQL, ClickHouse, and BigQuery with no card required. Each dialect also has its own sandbox, so you can test syntax in the database you actually want to learn.

Reference on this topic

In-depth articles with syntax and examples in the SQL Arena reference.

Frequently asked questions

What is an online SQL compiler?

An online SQL compiler is a browser-based environment where you can enter and execute SQL queries. The term is commonly used even though database engines typically parse, plan, and execute SQL rather than compile it like a traditional programming language.

Can I run SQL online without installing a database?

Yes. An online SQL environment provides a database engine or sandbox on the server side, so you can execute queries from the browser without setting up a local database.

What is an SQL sandbox?

An SQL sandbox is an isolated environment for experimenting with schemas, data, and queries. It is useful for learning syntax and checking how a query behaves without touching a production database.

Can I use an online SQL compiler for practice?

Yes. You can practice creating tables, filtering rows, joining tables, grouping data, and writing more complex queries. The available syntax depends on the SQL dialect supported by the environment.

What is an online SQL query compiler used for?

It is commonly used to test SQL syntax, reproduce a small data problem, experiment with a query, or practice SQL concepts. For meaningful tests, create representative tables and sample data rather than checking syntax alone.

See also

Practice queries with an online SQL compiler

Create your own tables, add test data, and run SQL in PostgreSQL, MySQL, ClickHouse, or BigQuery directly in the browser.

Open SQL sandbox

More practice from CodeRang