Why We Chose ClickHouse for Real-Time Analytics
When we built Aivena Data OS, we needed a database that could handle billions of rows with sub-second response times. After evaluating PostgreSQL (with TimescaleDB), Apache Druid, and ClickHouse, the choice became clear. ClickHouse is the undisputed king of performance and cost-efficiency for OLAP workloads.
Columnar vs. Row-Based Storage
Traditional databases (Postgres, MySQL) store data in rows. This is great for looking up a single record, but terrible for analytics where you need to aggregate a single column across billions of records.
In a columnar database, to calculate SUM(Amount), ClickHouse only reads Column 4 from disk. Postgres would have to read the entire table.
1. The Benchmarks: Real-World Performance
We ran a benchmark on a 1.2 billion row dataset (New York Taxi data) using a standard 3-node cluster.
| Query Type | PostgreSQL (Standard) | PostgreSQL (Timescale) | ClickHouse |
|---|---|---|---|
| Count Total | 480 seconds | 12 seconds | 0.08 seconds |
| Avg by Group | > 10 minutes | 45 seconds | 0.25 seconds |
| Complex Join | Time Out | 85 seconds | 1.2 seconds |
2. Expert Tip: Mastering the Primary Key
In ClickHouse's MergeTree engine, the primary key is not unique. It's a Sparse Index.
* Don't use high-cardinality columns (like UUID) as the first part of your primary key. This will bloat the index in memory.
* Do use columns with low-to-medium cardinality that you filter on most often (e.g., event_type, site_id, toStartOfDay(timestamp)).
A professional primary key strategy:
CREATE TABLE events (
event_type String,
timestamp DateTime,
user_id UInt64,
...
) ENGINE = MergeTree()
ORDER BY (event_type, toDate(timestamp), user_id);
This allows ClickHouse to skip entire "granules" of data during a scan, leading to massive performance gains.
3. How Aivena Enhances ClickHouse
Managing ClickHouse at scale is notoriously difficult (Zookeeper, shards, replicas, backups). On Aivena Data OS, we've automated the pain:
* Managed Sharding: Add a new node, and Aivena automatically handles the rebalancing of data across the cluster.
* CDC via Debezium: Use our visual builder to stream data from your production Postgres into ClickHouse in real-time.
* Automated Backups: We backup your parts to S3/MinIO every hour, ensuring zero data loss with one-click recovery.
Ready to experience the speed? Deploy ClickHouse on Aivena Data OS today.