Rockset vs. ClickHouse
for Real-Time Analytics

ClickHouse is an immutable, column-oriented data store. Rockset is fully mutable and uses its Converged Index™, which combines a columnar store, search index and row index to achieve low-latency analytics with maximum compute efficiency. Reduce infrastructure cost with a cloud-native architecture that disaggregates compute and storage. Save ops time and reduce complexity with a fully-managed real-time analytics database with no schema enforcement, clusters to manage, or any need to denormalize data.


Faster Queries

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


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.


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.



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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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.
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.
Compute and Storage
ClickHouse’s architecture does not separate storage, ingest compute and query compute.
ClickHouse cannot scale compute and storage resources independently, resulting in expensive overprovisioning, situations where imbalances or hotspots can occur, and the risk that a large number of small queries impacts an entire cluster.

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If you want flexible and easy real-time analytics, check out Rockset.

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


Efficient inserts, updates and deletes

Cloud-Native Architecture

Independent scaling of storage and compute in the cloud