---
title: union
description: |
  The `union` command concatenates the results from two or more datasets into
  one dataset. This allows users to combine results from multiple queries into
  one seamless dataset. One dataset can be a result set piped into the `union`
  command and then concatenated with another dataset.
url: https://coralogix.com/docs/dataprime/language-reference/commands-reference/union/
product: dataengine
feature: DataPrime Language
feature_id: dataprime-language
feature_identifier: dataengine/dataprime-language
last_updated: '2026-11-08'
---

# `union`

## Description

The `union` command concatenates the results from two or more datasets into one dataset. This allows users to combine results from multiple queries into one seamless dataset. One dataset can be a result set piped into the `union` command and then concatenated with another dataset.

## Syntax

```
<query> | union (<query>)
```

## Example 1

Combine logs from two different teams into a single dataset to analyze them together.

### Example data

```
// Logs for Team 58942

{ "id": "111", "name": "John" , "team.id": "58942" }

{ "id": "222", "name": "Emily", "team.id": "58942" }

{ "id": "333", "name": "Alice", "team.id": "58942" }



// Logs for Team 98361

{ "userid": "111", "timestamp": "2022-01-01T12:00:00Z", "team.id": "98361" }

{ "userid": "111", "timestamp": "2022-01-01T12:30:00Z", "team.id": "98361" }

{ "userid": "222", "timestamp": "2022-01-01T13:00:00Z", "team.id": "98361" }

{ "userid": "222", "timestamp": "2022-01-01T13:00:00Z", "team.id": "98361" }

{ "userid": "222", "timestamp": "2022-01-01T13:00:00Z", "team.id": "98361" }
```

### Example query

```
source logs(teamIds=['58942'])

| union (source logs(teamIds=['98361']))
```

### Example output

```
{ "id": "111", "name": "John" , "team.id": "58942" }

{ "id": "222", "name": "Emily", "team.id": "58942" }

{ "id": "333", "name": "Alice", "team.id": "58942" }

{ "userid": "111", "timestamp": "2022-01-01T12:00:00Z", "team.id": "98361" }

{ "userid": "111", "timestamp": "2022-01-01T12:30:00Z", "team.id": "98361" }

{ "userid": "222", "timestamp": "2022-01-01T13:00:00Z", "team.id": "98361" }

{ "userid": "222", "timestamp": "2022-01-01T13:00:00Z", "team.id": "98361" }

{ "userid": "222", "timestamp": "2022-01-01T13:00:00Z", "team.id": "98361" }
```

## Example 2

Compare how many records you have for the same timeframe across storage tiers. Because `frequentsearch` datasets are queryable like any other source, you can `union` your High (Frequent Search) tier with your `default` data, then use [\`dataspace()\`](https://coralogix.com/docs/dataprime/language-reference/functions-reference/general/dataspace.md) and [\`dataset()\`](https://coralogix.com/docs/dataprime/language-reference/functions-reference/general/dataset.md) to attribute each record to its origin and count per source in a single query.

### Example query

```
source frequentsearch/logs

| union (source logs)

| create query_source.dataspace from dataspace()

| create query_source.dataset from dataset()

| groupby query_source.dataspace, query_source.dataset agg count() as count
```

### Example output

```
{ "query_source": { "dataspace": "frequentsearch", "dataset": "logs" }, "count": 3996594 }

{ "query_source": { "dataspace": "default",        "dataset": "logs" }, "count": 11272291 }
```