Rockset vs. ClickHouse
for Real-Time Analytics

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ClickHouse is an immutable, column-oriented data store that was not built for the cloud. Rockset is cloud-native and separates compute-storage and compute-compute for fast, efficient search and analytics at scale. Under the hood, Rockset uses its fully mutable Converged Index™ – a columnar store, search index and row index – to achieve low-latency analytics with maximum compute efficiency.

1.67x

Faster Queries

Rockset is 1.67 times faster than ClickHouse with the same hardware configuration based on results from the Star Schema Benchmark.

20x

Faster Development Time

ClickHouse requires configuring nodes, shards, software versions, replication and more. Rockset is a fully-managed, cloud-native database which minimizes operational burden and ongoing maintenance.

50%+

Lower Infrastructure Costs

Rockset separates storage, ingest and query compute so you don’t need to overprovision resources for your workload. Additionally, Rockset’s Converged Index(™) is highly compute efficient.

SQL

Joins

Rockset supports full SQL, including joins, in an efficient way. In ClickHouse, joins are not a first class citizen and they are prohibitively expensive so you’ll need to use workarounds that add complexity to your data model.

Whatnot logo
Rockset offers ultimate flexibility for us to quickly experiment and build features.

Xin Xia, Marketplace and Discovery

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Command Alkon logo
We absolutely love Rockset. It’s a game changer for us.

Doug Moore, VP of Cloud

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Compute and Storage
ClickHouse is resource inefficient for real-time workloads.
ClickHouse’s architecture is built to batch load data for better compression and faster queries. As a result, ClickHouse cannot efficiently support high volume streaming ingestion and queries. In real-time scenarios, ingest and queries compete for the same pool of compute resources causing users to overprovision resources.
SQL-style JOINs
JOINs on ClickHouse are complex and expensive.
ClickHouse supports JOINs but cannot optimize them effectively. Denormalizing is recommended as an alternative, which requires data preparation that is expensive and complex.
Operational Burden
ClickHouse requires significant expertise and manual intervention.
ClickHouse’s use of indexing is limited to sparse indexes and skipping indexes, each of which must be manually configured by the user along nodes, shards, software versions, replication and more.
Mutability
ClickHouse is not mutable.
ClickHouse writes data to immutable files, called “parts.” This design helps ClickHouse achieve faster reads and writes, but mutations are expensive, as even small changes will cause large rewrites of entire parts.

Resources



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Rockset is built to exploit the efficiency of the cloud for real-time analytics, delivering consistent performance at a fraction of the cost.

Here are four reasons why:

Converged Indexing™

Creation of search, columnar and row indexes at ingest time

Full SQL

SQL search, aggregations and joins on semi-structured data

Mutability

Efficient inserts, updates and deletes

Cloud-Native Architecture

Independent scaling of storage-compute and compute-compute