ClickHouse vs. Firebolt

Many ClickHouse users struggle with its non-standard dialect and significant engineering efforts required to achieve fast performance. Firebolt’s cloud data warehouse combines sub-second speed with the ease of use of ANSI SQL to power a range of analytics use cases. Use Firebolt to unify data processing and serving on a single platform while reducing operational complexity and optimizing costs.

Redshift vs Firebolt

Firebolt provides consistent sub-second query performance across diverse data applications.

Jeremy Stroud
Director IT Architecture

Firebolt

ClickHouse

Performance
Fastest performance for complex analytics
  • Advanced history-based query optimization and JOIN acceleration
  • Highly efficient data reading **?
  • ACID transactions designed with performance in mind
***
  • Limited JOIN performance
  • Lacks a native query optimizer
  • Limited set of indexes
Cost
Consistently best price/performance
  • Unified processing and serving significantly lowers TCO
  • Extremely cost-efficient JOINs
  • Standard SQL is easy to work with, minimizing operational costs
***?
  • High cost of maintaining a general-purpose DWH for processing and an accelerator for serving
  • JOINs and mutations are expensive
  • High cost of specialized staff to operate non-standard SQL dialect
Flexibility & Ease of Use
Simple to use with high flexibility
  • Fully ANSI-SQL compliant
  • Can provision different cluster types on same data for workload isolation and segmentation *?
Non-standard with a steep learning curve
  • Requires significant expertise
  • Not ANSI-SQL compliant
Use cases
Processing and serving latency-sensitive analytics
*****?
Performance

Firebolt

Sub-second performance for processing and serving
  • Fast performance for large-scale data processing and serving
  • Advanced query optimization and JOIN acceleration
  • Advanced indexing capabilities
  • ACID transactions designed with performance in mind

ClickHouse

Good performance for serving
  • Fast performance for real-time data serving
  • Limited JOIN performance
  • Lacks a native query optimizer
  • Limited set of indexes
Cost

Firebolt

Consistently best price/performance
  • Unified processing and serving significantly lowers TCO
  • Extremely cost-efficient JOINs
  • Standard SQL is cost-effective to work with

ClickHouse

Cost-effective for real-time analytics
  • High cost of maintaining a general-purpose DWH for processing and an accelerator for serving
  • JOINs and mutations are expensive
  • High cost of specialized staff to operate non-standard SQL dialect
Flexibility & Ease of Use

Firebolt

Simple to use with high flexibility
  • Fully ANSI-SQL compliant
  • Can provision different cluster types on same data for workload isolation and segmentation

ClickHouse

Non-standard with a steep learning curve
  • Requires significant expertise
  • Not ANSI-SQL compliant
Use cases

Firebolt

Processing and serving latency-sensitive analytics

ClickHouse

Serving real-time data

Unify data processing and serving

Data engineering teams often rely on separate systems - a general-purpose data warehouse for transforming, and an accelerator like ClickHouse for serving. This leads to the need for specialized skills, fragmented data silos, redundant data and data flows, and skyrocketing costs. Firebolt combines the capabilities of a data warehouse with the power of a query accelerator to streamline your architecture, eliminate data duplication, and significantly lower TCO.

Amazon redshift firebolt comparison table

Talk to a Firebolt Expert