ClickHouse vs. PostgreSQL: Scaling Analytical Queries to 100M+ Rows
A technical benchmark comparing row-oriented PostgreSQL against columnar ClickHouse for real-time analytics, aggregations, and high-throughput event ingestion.
Abdul Majid
Lead Data Engineer & Data Scientist
Executive Engineering Summary & Takeaways
- PostgreSQL excels at OLTP transactions (ACID), but slows down exponentially on aggregations over 10M+ rows.
- ClickHouse columnar vectorized execution delivers 50x-100x faster analytical query execution with 5x-8x data compression.
- A CDC pipeline with Kafka and Debezium syncs transactional tables to ClickHouse in near-real-time without locking Postgres.
1. Why Row-Oriented Databases Choke on Analytics
In PostgreSQL, data is stored row-by-row on disk pages. For analytical aggregations over 100M rows, ClickHouse scans columnar data with vectorized SIMD instructions in 74 milliseconds, compared to 24+ seconds in Postgres.
CREATE TABLE default.telemetry_events (
event_id UUID,
client_id LowCardinality(String),
event_type LowCardinality(String),
duration_ms Float32,
response_code UInt16,
event_timestamp DateTime64(3, 'UTC')
) ENGINE = MergeTree()
PARTITION BY toYYYYMM(event_timestamp)
ORDER BY (client_id, event_type, event_timestamp);Ready to Upgrade Your Cloud Infrastructure?
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