Analytics Database Basic Auth

ClickHouse REST API

High-performance columnar database for real-time analytics

ClickHouse is an open-source column-oriented database management system designed for online analytical processing (OLAP). It enables real-time analytics on petabytes of data with sub-second query response times. Developers use ClickHouse for building analytics dashboards, event logging systems, time-series analysis, and business intelligence applications that require fast aggregations and complex analytical queries.

Base URL https://your-cluster.clickhouse.cloud:8443

API Endpoints

Method	Endpoint	Description
GET	`/`	Execute a SELECT query and retrieve results in various formats (JSON, CSV, TabSeparated)
POST	`/`	Execute INSERT, CREATE, DROP, ALTER and other SQL statements via HTTP POST
GET	`/?query={sql}`	Execute a query using URL parameter with automatic format detection
POST	`/?query=INSERT INTO table FORMAT JSONEachRow`	Insert data in JSON format (one JSON object per line)
GET	`/?query=SELECT * FROM system.tables`	List all tables in the database using system tables
GET	`/?query=SELECT * FROM system.databases`	List all databases in the ClickHouse instance
GET	`/?query=SHOW CREATE TABLE {table}`	Get the CREATE TABLE statement for a specific table
GET	`/?query=SELECT * FROM system.columns WHERE table='{table}'`	Get column information and metadata for a specific table
GET	`/?query=SELECT * FROM system.query_log`	Retrieve query execution history and performance metrics
POST	`/?query=CREATE TABLE {table}`	Create a new table with specified schema and engine
POST	`/?query=ALTER TABLE {table}`	Modify table structure, add/drop columns, or change settings
GET	`/?query=SELECT * FROM system.parts`	Get information about data parts in MergeTree tables for optimization
GET	`/?query=SELECT * FROM system.metrics`	Retrieve current system metrics and performance indicators
POST	`/?query=OPTIMIZE TABLE {table}`	Trigger manual optimization and merging of table data parts
GET	`/ping`	Health check endpoint to verify server availability

Code Examples

# Query data from ClickHouse
curl -u default:your_password \
  'https://your-cluster.clickhouse.cloud:8443/?query=SELECT%20count()%20FROM%20events%20WHERE%20date%20=%20today()%20FORMAT%20JSON'

# Insert data into ClickHouse
curl -u default:your_password \
  -X POST 'https://your-cluster.clickhouse.cloud:8443/?query=INSERT%20INTO%20events%20FORMAT%20JSONEachRow' \
  -d '{"user_id":123,"event_type":"click","timestamp":"2024-01-15 10:30:00"}'

# Create a table
curl -u default:your_password \
  -X POST 'https://your-cluster.clickhouse.cloud:8443/' \
  -d 'CREATE TABLE analytics.events (user_id UInt64, event_type String, timestamp DateTime) ENGINE = MergeTree() ORDER BY timestamp'

// Query ClickHouse using fetch
const queryClickHouse = async (sql) => {
  const auth = btoa('default:your_password');
  const response = await fetch(
    `https://your-cluster.clickhouse.cloud:8443/?query=${encodeURIComponent(sql)}&default_format=JSON`,
    {
      headers: {
        'Authorization': `Basic ${auth}`
      }
    }
  );
  return await response.json();
};

// Execute a SELECT query
const results = await queryClickHouse(
  'SELECT count() as total FROM events WHERE date = today()'
);
console.log(results);

// Insert data
const insertData = async (records) => {
  const auth = btoa('default:your_password');
  const body = records.map(r => JSON.stringify(r)).join('\n');
  await fetch(
    'https://your-cluster.clickhouse.cloud:8443/?query=INSERT INTO events FORMAT JSONEachRow',
    {
      method: 'POST',
      headers: {
        'Authorization': `Basic ${auth}`,
        'Content-Type': 'application/x-ndjson'
      },
      body: body
    }
  );
};

await insertData([
  {user_id: 123, event_type: 'click', timestamp: '2024-01-15 10:30:00'},
  {user_id: 456, event_type: 'view', timestamp: '2024-01-15 10:31:00'}
]);

import requests
from requests.auth import HTTPBasicAuth
import json

# Initialize connection
url = 'https://your-cluster.clickhouse.cloud:8443'
auth = HTTPBasicAuth('default', 'your_password')

# Execute a SELECT query
def query_clickhouse(sql):
    response = requests.get(
        url,
        params={'query': sql, 'default_format': 'JSON'},
        auth=auth
    )
    return response.json()

# Get event count
result = query_clickhouse(
    "SELECT count() as total FROM events WHERE date = today()"
)
print(f"Total events: {result['data'][0]['total']}")

# Insert data
def insert_data(table, records):
    data = '\n'.join(json.dumps(r) for r in records)
    response = requests.post(
        url,
        params={'query': f'INSERT INTO {table} FORMAT JSONEachRow'},
        auth=auth,
        data=data.encode('utf-8')
    )
    return response.status_code == 200

# Insert events
events = [
    {'user_id': 123, 'event_type': 'click', 'timestamp': '2024-01-15 10:30:00'},
    {'user_id': 456, 'event_type': 'view', 'timestamp': '2024-01-15 10:31:00'}
]
insert_data('events', events)

# Create a table
def create_table():
    sql = '''
    CREATE TABLE IF NOT EXISTS analytics.events (
        user_id UInt64,
        event_type String,
        timestamp DateTime,
        properties String
    ) ENGINE = MergeTree()
    ORDER BY (timestamp, user_id)
    '''
    requests.post(url, params={'query': sql}, auth=auth)

create_table()

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clickhouse_query Execute analytical SQL queries on ClickHouse databases and return aggregated results in JSON format

clickhouse_insert Insert event data, logs, or metrics into ClickHouse tables with automatic batching and format conversion

clickhouse_schema_inspector Inspect database schemas, list tables, columns, and data types to understand available data structures

clickhouse_performance_analyzer Analyze query performance, execution times, and resource usage from system tables for optimization recommendations

clickhouse_table_manager Create, modify, and optimize ClickHouse tables with appropriate engines and partitioning strategies

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ClickHouse REST API

API Endpoints

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Code Examples

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