ClickHouse Protocol Documentation
This directory contains consolidated documentation for HeliosDB's ClickHouse protocol support.
Quick Start
Connect to HeliosDB using any ClickHouse client:
from clickhouse_driver import Client
# Connect to HeliosDB (ClickHouse-compatible)
client = Client(
host='localhost',
port=9000,
user='default',
password='',
database='default'
)
# Execute query
result = client.execute('SELECT count() FROM events')
print(f"Total events: {result[0][0]}")
Contents
| File |
Description |
| README.md |
Overview and quick start (this file) |
| CONFIGURATION.md |
Connection and protocol configuration |
| COMPATIBILITY.md |
ClickHouse feature compatibility |
| EXAMPLES.md |
Query and analytics examples |
Feature Overview
Protocol Support
| Feature |
Status |
Notes |
| Native Protocol (TCP) |
100% |
Port 9000 |
| HTTP Protocol |
100% |
Port 8123 |
| Compression |
Supported |
LZ4, ZSTD |
| SSL/TLS |
Supported |
Secure connections |
Table Engines
| Engine |
Coverage |
Notes |
| MergeTree |
100% |
Primary engine |
| ReplacingMergeTree |
100% |
Upsert support |
| AggregatingMergeTree |
100% |
Pre-aggregation |
| SummingMergeTree |
100% |
Auto-summing |
| Distributed |
100% |
Multi-node queries |
Query Features
| Feature |
Status |
Notes |
| PREWHERE |
Supported |
Early filtering |
| SAMPLE |
Supported |
Data sampling |
| FINAL |
Supported |
Deduplication |
| Materialized Views |
Supported |
Auto-aggregation |
| Window Functions |
Supported |
Analytics |
Connection Parameters
| Parameter |
Default |
Description |
host |
localhost |
Server hostname |
port |
9000 |
Native protocol port |
http_port |
8123 |
HTTP protocol port |
user |
default |
Username |
password |
- |
Password |
database |
default |
Database name |
compression |
lz4 |
Compression type |
Driver Compatibility
| Driver |
Version |
Status |
| clickhouse-driver (Python) |
0.2+ |
Full |
| clickhouse-go (Go) |
2.x |
Full |
| @clickhouse/client (Node.js) |
0.2+ |
Full |
| ClickHouse JDBC |
0.4+ |
Full |
Use Cases
- Real-time Analytics: Sub-second query response
- Log Analysis: Full-text search + aggregation
- Time-Series: Metrics and monitoring
- OLAP Queries: Complex aggregations
- Data Lakes: S3/GCS integration
| Operation |
Speed |
Notes |
| count() |
11.7M rows/ms |
1B rows in 85ms |
| GROUP BY |
4.1M rows/ms |
100K groups |
| Bulk Insert |
1.5M rows/sec |
100K batches |
Last Updated: December 2025
Consolidation Status: Complete