According to our (Global Info Research) latest study, the global Open Source Time Series Database market size was valued at US$ 2439 million in 2025 and is forecast to a readjusted size of US$ 3687 million by 2032 with a CAGR of 6.2% during review period.
Open-source time-series databases are a type of database system specifically designed for storing, managing, and analyzing time-series data. This data typically consists of timestamps and related values, recording changes in chronological order. Renowned for their efficient data writing, querying, and compression capabilities, open-source time-series databases are widely used in real-time monitoring, the Internet of Things (IoT), financial analysis, and environmental monitoring. As open-source software, they offer flexible customization and deployment options, allowing developers and enterprises to tailor system functionality to specific needs while enjoying community support and continuous innovation. The downstream applications of open-source time-series databases primarily target industries with strong demands for high-frequency data acquisition, real-time analysis, and continuous writing capabilities, including industrial IoT, smart manufacturing, energy and power monitoring, communications operations and maintenance, smart cities, financial risk control, connected vehicles, and environmental monitoring. These sectors rely on open-source TSDBs to build low-cost, highly scalable data infrastructure for monitoring, alerting, predictive maintenance, and visualization analysis. Due to the free nature of open-source solutions and intense competition, downstream revenue primarily comes from enterprise-level versions, cloud hosting services, operations and maintenance support, and ecosystem components; therefore, the overall gross profit margin is generally around 63%.
Open source time series databases are rapidly becoming a key component of modern data infrastructure, especially in areas that require real-time data processing and analysis. With the popularity of the Internet of Things, cloud computing, and big data, enterprises have a growing demand for efficient, scalable, and flexible time series data management. Open source time series databases not only meet these needs, but also promote the expansion of innovation and diverse applications through their community-driven development model. However, as data continues to expand in size and complexity, how to optimize performance and ensure data consistency and security will become an important challenge for the future development of open source time series databases.
This report is a detailed and comprehensive analysis for global Open Source Time Series Database market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.
Key Features:
Global Open Source Time Series Database market size and forecasts, in consumption value ($ Million), 2021-2032
Global Open Source Time Series Database market size and forecasts by region and country, in consumption value ($ Million), 2021-2032
Global Open Source Time Series Database market size and forecasts, by Type and by Application, in consumption value ($ Million), 2021-2032
Global Open Source Time Series Database market shares of main players, in revenue ($ Million), 2021-2026
The Primary Objectives in This Report Are:
To determine the size of the total market opportunity of global and key countries
To assess the growth potential for Open Source Time Series Database
To forecast future growth in each product and end-use market
To assess competitive factors affecting the marketplace
This report profiles key players in the global Open Source Time Series Database market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include InfluxData, TigerData, Prometheus, OpenTSDB, VictoriaMetrics, QuestDB, TaosData, Timecho, Apache Software Foundation, Prometheus, etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Market segmentation
Open Source Time Series Database market is split by Type and by Application. For the period 2021-2032, the growth among segments provides accurate calculations and forecasts for Consumption Value by Type and by Application. This analysis can help you expand your business by targeting qualified niche markets.
Market segment by Type
Cloud-Based
On-Premises
Market segment by Data Model
Relational-Based
Column-Based
Others
Market segment by Distributed
Standalone
Distributed
Market segment by Application
Internet of Things Industry
Financial Industry
Telecommunication Industry
Others
Market segment by players, this report covers
InfluxData
TigerData
Prometheus
OpenTSDB
VictoriaMetrics
QuestDB
TaosData
Timecho
Apache Software Foundation
Prometheus
Cortex
GridDB
Market segment by regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia, Italy and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia and Rest of Asia-Pacific)
South America (Brazil, Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Open Source Time Series Database product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Open Source Time Series Database, with revenue, gross margin, and global market share of Open Source Time Series Database from 2021 to 2026.
Chapter 3, the Open Source Time Series Database competitive situation, revenue, and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and by Application, with consumption value and growth rate by Type, by Application, from 2021 to 2032.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2021 to 2026.and Open Source Time Series Database market forecast, by regions, by Type and by Application, with consumption value, from 2027 to 2032.
Chapter 11, market dynamics, drivers, restraints, trends, Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Open Source Time Series Database.
Chapter 13, to describe Open Source Time Series Database research findings and conclusion.
Summary:
Get latest Market Research Reports on Open Source Time Series Database. Industry analysis & Market Report on Open Source Time Series Database is a syndicated market report, published as Global Open Source Time Series Database Market 2026 by Company, Regions, Type and Application, Forecast to 2032. It is complete Research Study and Industry Analysis of Open Source Time Series Database market, to understand, Market Demand, Growth, trends analysis and Factor Influencing market.