UDC 004.65
TIME SERIES DATABASES: REVIEW, COMPARATIVE ANALYSIS, APPLICATIONS
V. N. Kalinin, Assistant, Department of Telecommunications, Institute of Radioelectronics and Informatics,
MIREA – Russian Technological University, Moscow, Russia;
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K. B. Dedushenko, Dr. in Physics and Mathematics, Senior Researcher, Professor, Department of Telecommunications, Institute of Radioelectronics and Informatics, MIREA – Russian Technological University,
Moscow, Russia;
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R. A. Vodolazhenko, PhD in technical sciences, Associate Professor, Department of Applied Mathematics, Synergy University, Moscow, Russia;
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The article presents an experimental comparison of six DBMSs for time series data: InfluxDB,
OpenTSDB, TimescaleDB, PostgreSQL, Microsoft SQL Server, and MongoDB. Testing was performed on a
single-node testbed (Ubuntu 22.04, i7-6700K, 64 GB RAM, SSD+HDD) using a unified data schema (id,
metric, timestamp, value). The study measured write throughput with varying batch sizes and numbers of
threads, the stability of long-running data ingestion under different loads, and response time for intervalbased
queries and aggregation queries. Heterogeneous metrics were normalized using the geometric mean
of ratios and aggregated into weighted priority profiles. As a result, specialized TSDBs demonstrated best
performance: InfluxDB showed the highest write throughput and stability, TimescaleDB maintained competitive
write performance and demonstrated read latencies close to InfluxDB, while OpenTSDB showed
good write performance but lagged behind in data retrieval. PostgreSQL and MS SQL Server demonstrated
average results, whereas MongoDB showed lowest performance.
Key words: time-series databases, time series, comparative analysis, DBMS benchmarking, load testing,
DBMS performance.