> ## Documentation Index
> Fetch the complete documentation index at: https://private-7c7dfe99-fix-nav-issues.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Insert data into ClickHouse Cloud using clickhouse-client
> Learn how to use clickhouse-client to insert data from local CSV and Parquet files into a ClickHouse Cloud service from the command line.
All quickstarts
Real-Time Analytics
Data Warehousing
Observability
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Cloud
Prerequisites
You should also have completed the following quickstarts:
* [Create your first Cloud service](/get-started/quickstarts/create-your-first-service-on-cloud) - you'll need a running ClickHouse Cloud service to insert data into
* [Obtain your Cloud connection details](/get-started/quickstarts/obtain-your-cloud-connection-details) - you'll need your hostname, username and password to connect
What you'll build
In this quickstart you'll use **clickhouse-client** - the official ClickHouse CLI client - to insert data from a local CSV file into a ClickHouse Cloud service.
You'll install clickhouse-client, prepare a sample dataset, connect to your Cloud service, create a table, and insert data from your local machine.
By the end, you'll know how to use clickhouse-client to load local files into ClickHouse Cloud, a workflow that works with CSV, Parquet, JSON, and many other formats.
### Install clickhouse-client
`clickhouse-client` is the official CLI for connecting to ClickHouse. It is included in the ClickHouse binary.
Install it using the universal installer:
```bash theme={null}
curl https://clickhouse.com/ | sh
```
This downloads the latest `clickhouse` binary into your current directory. Verify the installation:
```bash theme={null}
./clickhouse client --version
```
You should see output showing the ClickHouse version number, confirming `clickhouse-client` is ready to use.
### Prepare a sample CSV file
Create a small sample CSV file so this quickstart is self-contained. Run the following in your terminal:
```bash theme={null}
cat <<'EOF' > sample_data.csv
timestamp,event_type,user_id,duration_ms,status
2024-01-15 10:30:00,page_view,1001,120,success
2024-01-15 10:31:15,click,1002,45,success
2024-01-15 10:32:00,page_view,1003,200,success
2024-01-15 10:33:30,purchase,1001,1500,success
2024-01-15 10:34:00,click,1004,60,error
2024-01-15 10:35:45,page_view,1002,95,success
2024-01-15 10:36:10,purchase,1005,2200,success
2024-01-15 10:37:00,click,1003,30,success
2024-01-15 10:38:20,page_view,1004,150,error
2024-01-15 10:39:00,purchase,1002,1800,success
EOF
```
### Connect to your Cloud service
The commands below assume you've exported `CLICKHOUSE_HOST`, `CLICKHOUSE_USER`, and `CLICKHOUSE_PASSWORD` as environment variables, as described in the [Obtain your Cloud connection details](/get-started/quickstarts/obtain-your-cloud-connection-details) quickstart. If you haven't, you can replace them with your values directly.
Test connectivity by running a simple query against your Cloud service:
```bash theme={null}
./clickhouse client \
--host $CLICKHOUSE_HOST \
--port 9440 \
--user $CLICKHOUSE_USER \
--password $CLICKHOUSE_PASSWORD \
--secure \
-q "SELECT 1"
```
If the connection succeeds you'll see `1` printed to the terminal. If you get a connection error, check that your service is awake in the Cloud console and that your hostname and password are correct.
Port `9440` is the secure native protocol port for ClickHouse Cloud. The `--secure` flag enables TLS encryption. These are required for all Cloud connections.
### Create a target table and insert data
First, create a table on your Cloud service to receive the data:
```bash theme={null}
./clickhouse client \
--host $CLICKHOUSE_HOST \
--port 9440 \
--user $CLICKHOUSE_USER \
--password $CLICKHOUSE_PASSWORD \
--secure \
-q "
CREATE TABLE IF NOT EXISTS events (
timestamp DateTime,
event_type LowCardinality(String),
user_id UInt32,
duration_ms UInt32,
status LowCardinality(String)
)
ENGINE = MergeTree
ORDER BY (event_type, timestamp)
"
```
Now insert the data from your local CSV file. This is the key step - `clickhouse-client` reads the file from stdin and streams it to the remote service:
```bash theme={null}
./clickhouse client \
--host $CLICKHOUSE_HOST \
--port 9440 \
--user $CLICKHOUSE_USER \
--password $CLICKHOUSE_PASSWORD \
--secure \
-q "INSERT INTO events FORMAT CSVWithNames" < sample_data.csv
```
`clickhouse-client` sends the contents of the CSV file directly to your Cloud service. The `CSVWithNames` format tells ClickHouse that the first row contains column headers.
### Verify the data was inserted
Query your Cloud service to confirm the rows arrived:
```bash theme={null}
./clickhouse client \
--host $CLICKHOUSE_HOST \
--port 9440 \
--user $CLICKHOUSE_USER \
--password $CLICKHOUSE_PASSWORD \
--secure \
-q "SELECT count() FROM events"
```
You should see `10` - the number of rows in the sample CSV.
Preview the data:
```bash theme={null}
./clickhouse client \
--host $CLICKHOUSE_HOST \
--port 9440 \
--user $CLICKHOUSE_USER \
--password $CLICKHOUSE_PASSWORD \
--secure \
-q "SELECT * FROM events ORDER BY timestamp LIMIT 5"
```
This same workflow works with Parquet, TSV, JSON, Avro, ORC, and many other [supported formats](/reference/formats/index) - just change the `FORMAT` clause and pipe in the appropriate file.
Next steps
In this quickstart you installed `clickhouse-client`, connected it to a ClickHouse Cloud service, and used it to stream data from a local CSV file into the Cloud. This same approach works for Parquet, JSON, and dozens of other formats.
Check out the following quickstarts next:
* [Create your first MergeTree table](/get-started/quickstarts/create-your-first-mergetree-table)
Or go deeper with the reference documentation:
* [clickhouse-client reference](/concepts/features/interfaces/cli)
* [Supported input/output formats](/reference/formats/index)
