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.
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.
Comparing ClickHouse vs Rockset for Event and CDC Streams
Rockset Beats ClickHouse and Druid on the Star Schema Benchmark (SSB)
Compare real-time analytics databases in 2023: Rockset, Apache Druid, ClickHouse, Pinot
Change Data Capture: What It Is and How to Use It
Introducing Compute-Compute Separation for Real-Time Analytics
Introducing Vector Search on Rockset: How to run semantic search with OpenAI and Rockset
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:
Creation of search, columnar and row indexes at ingest time
SQL search, aggregations and joins on semi-structured data
Efficient inserts, updates and deletes
Independent scaling of storage-compute and compute-compute