Benchmarking Specialized Databases for High-frequency Data

This paper presents a benchmarking suite designed for the evaluation and comparison of time series databases for high-frequency data, with a focus on financial applications. The proposed suite comprises of four specialized databases: ClickHouse, InfluxDB, kdb+ and TimescaleDB. The results from the suite demonstrate that kdb+ has the highest performance amongst the tested databases, while also highlighting the strengths and weaknesses of each of the databases. The benchmarking suite was designed to provide an objective measure of the performance of these databases as well as to compare their capabilities for different types of data. This provides valuable insights into the suitability of different time series databases for different use cases and provides benchmarks that can be used to inform system design decisions.

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Publication Details

Journal
The Journal of FinTech
Published
2025-03-01
DOI
https://doi.org/10.1142/s2705109925500026
Primary Topic
Advanced Database Systems and Queries
Type
article
Field-Weighted Citation Impact
0.00
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article

Benchmarking Specialized Databases for High-frequency Data

Fazl Barez, Paul Bilokon, Ruijie Xiong
The Journal of FinTech
Advanced Database Systems and Queries
article

Benchmarking Specialized Databases for High-frequency Data

Fazl Barez, Paul Bilokon, Ruijie Xiong
article en

Abstract

This paper presents a benchmarking suite designed for the evaluation and comparison of time series databases for high-frequency data, with a focus on financial applications. The proposed suite comprises of four specialized databases: ClickHouse, InfluxDB, kdb+ and TimescaleDB. The results from the suite demonstrate that kdb+ has the highest performance amongst the tested databases, while also highlighting the strengths and weaknesses of each of the databases. The benchmarking suite was designed to provide an objective measure of the performance of these databases as well as to compare their capabilities for different types of data. This provides valuable insights into the suitability of different time series databases for different use cases and provides benchmarks that can be used to inform system design decisions.

The Journal of FinTechVol. 05(01)
Imperial College London (GB), University of Edinburgh (GB)
Openalex Percentile: Top 96%
Advanced Database Systems and Queries
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Benchmarking Specialized Databases for High-frequency Data — Fazl Barez, Paul Bilokon, et al. · The Journal of FinTech (2025) | TGRS Research Map | TGRS