Time Series Databases (TSDB) Software For BFSI Sector Market size was valued at USD 106.74 Million in 2023 and is projected to reach USD 235.99 Million by 2030, growing at a CAGR of 10.53% from 2024 to 2030.

Global Time Series Databases (TSDB) Software For BFSI Sector Market Overview

The need to handle and analyze time-stamped data in various industries, including finance, led to the emergence of time series databases. Traditional relational databases needed better suited for efficiently managing large volumes of time-series data. The banking, financial services, and insurance (BFSI) sector is undergoing a data revolution driven by the exponential growth of time-series data. This data, which captures trends and changes over time, is invaluable for everything from understanding customer behavior to managing risk and making investment decisions. As a result, the demand for robust and scalable time series databases (TSDBs) is skyrocketing in the BFSI sector.

The history of TSDBs in the BFSI sector can be traced back to the early days of electronic trading when the need for high-speed data capture and analysis became apparent. Early TSDBs were often custom-built solutions designed to meet the specific needs of individual financial institutions. However, the rise of cloud computing and big data has led to a new generation of commercial TSDBs that are more affordable, scalable, and easier to use. The BFSI sector generates massive amounts of time-series data from transactions, market movements, customer behavior, and operational systems. Traditional relational databases struggle to handle this data efficiently, making TSDBs essential for storage, retrieval, and analysis.

Regulations like Basel III and IFRS 17 necessitate comprehensive data storage and analysis capabilities. TSDBs facilitate efficient recordkeeping, risk management, and compliance reporting for BFSI institutions. Timely insights into market trends, customer behavior, and fraud detection are crucial for competitive advantage. TSDBs enable real-time data capture, analysis, and prediction, powering AI-driven applications for personalized banking, fraud prevention, and dynamic risk management.

The global Open Source Time Series Database (TSDB) market size was valued at USD 447.17 million in 2025 and is projected to reach USD 1,922.95 million by 2033, growing at a CAGR of 19.9% from 2025 to 2033. The growing adoption of IoT devices, the increasing need for real-time data analysis, and the rise of the Industrial Internet of Things (IIoT) are driving the growth of the Open Source TSDB market. Cloud-based TSDBs are expected to witness the fastest growth during the forecast period due to their scalability, cost-effectiveness, and ease of use. IoT industry is the largest application segment, and the financial industry is expected to witness the fastest growth during the forecast period. North America held the largest market share in 2025, and Asia Pacific is expected to register the highest CAGR during the forecast period. The key players in the Open Source TSDB market include InfluxData, Timescale, Prometheus, OpenTSDB, VictoriaMetrics, and QuestDB.

Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which can contain up to several gigabytes of data. Surprisingly, research on MTS search is very limited. Most existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two provably correct algorithms to solve this problem — (1) an R-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences, and (2) a List Based Search (LBS) algorithm which uses sorted lists for indexing. We demonstrate the performance of these algorithms using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>95%) thus needing actual disk access for only less than 5% of the observations. To the best of our knowledge, this is the first flexible MTS search algorithm capable of subsequence search on any subset of variables. Moreover, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

The dataset included with this article contains three files describing and defining the sample and variables for VAT impact, and Excel file 1 consists of all raw and filtered data for the variables for the panel data sample. Excel file 2 depicts time-series and cross-sectional data for nonfinancial firms listed on the Saudi market for the second and third quarters of 2019 and the third and fourth quarters of 2020. Excel file 3 presents the raw material of variables used in measuring the company's profitability of the panel data sample

Rosalia Times Series Database

The BOKU (University of Natural Resources and Life Sciences Vienna) university demonstration forest Rosalia with an area of 950 ha has been used for research and education since 1875. In 2013 – upon an initiative of a group of researchers in various disciplines – it was decided to extend the so far mainly forestry oriented activities by implementing a hydrological experimental research watershed. The overall objective is to collect data that support the study of transport processes in the system of soil, water, plants and atmosphere. More specifically, emphasis is on bridging the gap between point related measurements and effective values and parameters required for modelling flow and transport processes in watersheds.

2 Objectives

The main objectives for the research watershed are

• to collect data that support the study of transport processes in the system of soil, water, plants and atmosphere
• emphasis is on bridging the gap between point related measurements and effective values and parameters for modelling watersheds of various sizes
• to generate comprehensive reference information for research projects on future management and climate change impacts

Operation is planned for a period of at least 10 years using only internal resources of the university, to avoid potential interruptions due to project-based short-term availability of personal and financial resources.

The objective of this article is to present the research watershed, the data collected and to make these data accessible to the research community.

Cyprus CY: Number of Listed Domestic Companies: Total data was reported at 92.000 Unit in 2022. This stayed constant from the previous number of 92.000 Unit for 2021. Cyprus CY: Number of Listed Domestic Companies: Total data is updated yearly, averaging 93.500 Unit from Dec 1993 (Median) to 2022, with 30 observations. The data reached an all-time high of 141.000 Unit in 2006 and a record low of 35.000 Unit in 1994. Cyprus CY: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cyprus – Table CY.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.;World Federation of Exchanges database.;Sum;Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

The size and share of the market is categorized based on Type (Relational Database Server, Time Series Database Server, Object Oriented Database Server, Navigational Database Server) and Application (Education, Financial Services, Healthcare, Government, Life Sciences, Manufacturing, Retail, Utilities, Others) and geographical regions (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa).

Abstract

The central statistical offices in most countries place heavy emphasis on constructing sound databases for all activities within the services sector. PCBS’ Services Statistics Program is part of the Economic Statistics Program, which is part of the larger program for establishing the System of Official Statistics for Palestine. PCBS initiated, in the reference year 1994, the economic surveys series. The series includes, in addition to the services survey, surveys on industry, internal trade construction-contractors, and transport and storage sectors for the purpose of establishing a time series database of economic activities in line with international recommendations specified in System of National Account (SNA) 93 and in the UN manual for Services Statistics.

Objectives: The objective of the survey was to obtain data on:

1. Number of enterprises and persons engaged in services by activity and location.
2. Value of output, intermediate consumption and stocks.
3. Value added components.
4. Payments and transfers.
5. Capital formation.
6. Contribution of the surveyed activities to the GDP and other National Accounts variables.

Target Population

PCBS depends on the International and Industrial Classification of all economic activities, version 3, (ISIC - 3) by the United Nation to classify the economic activities. The services survey covers the following activities: 1. Hotels and restaurants 2. Real estate, renting and business activities 3. Education 4. Health and social work 5. Other community, social and personal service activities

Geographic coverage

West Bank and Gaza Strip.

Analysis unit

Enterprise constitutes the primary sampling unit (PSU)

Universe

Enterprise: It is an economic entity that is capable, in its own right, of owning assets, incurring liabilities and engaging in economic activities and in transactions with other entities. Includes enterprise related to household and branches, and enterprise related to non-financial companies sector.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the Services Survey is a single-stage stratified random - systematic sample in which the enterprise constitutes the primary sampling unit (PSU). Three levels of strata were used to arrive at an efficient representative sample (i.e. economic activity, size of employment and geographical levels).

The sample size amounted to 1,522 enterprises out of the 12,970 enterprises that comprise the survey frame.

Mode of data collection

Face-to-face [f2f]

Research instrument

Survey Questionnaire

There is one form of the services survey questionnaire 2000, related to household and branches, and the non-finance companies sector. The questionnaire contains the following main variables: 1. Number of employees in a company and their compensations. 2. The output of the main and second activities. 3. Goods production inputs. 4. Various payments and transfers. 5. Indirect taxes. 6. Enterprises assets.

Cleaning operations

Data processing: For ensuring quality and consistency of data, a set of measures were taken into account for strengthening accuracy of data as follows: - Preparing data entry program before data collection for checking readiness of the program for data entry. - A set of validation rules were applied on the program for checking consistency of data. - Efficiency of the program was checked through pre-testing in entering few questionnaires, including incorrect information for checking its efficiency in capturing these information. - Well trained data keyers were selected and trained for the main data entry. - Weekly or biweekly data files were received by project management for checking accuracy and consistency, notes of correction were provided for data entry management for correction.

Response rate

82%

Sampling error estimates

Statistical Errors: The findings of the survey are affected by statistical errors due to using sampling in conducting the survey for the units of the target population, which increases the chances of having variances from the actual values we expect to obtain from the data had we conducted the survey using comprehensive enumeration. The variance of the key goods in the survey was computed and dissemination was carried out on the level of the Palestinian Territory for reasons related to sample design and computation of the variance of the different indicators.

Non-Statistical Errors These types of errors could appear on one or all the survey stages that include data collection and data entry: Response errors: these types of errors are related to, responders, fieldworkers, and data entry personnel's. And to avoid mistakes and reduce the impact has been a series of actions that would enhance the accuracy of the data through a process of data collection from the field and the data processing.

Focuses on financial flows, trends in external debt, and other major financial indicators for developing and advanced economies (data from Quarterly External Debt Statistics and Quarterly Public Sector Debt databases). Includes over 200 time series indicators from 1970 to 2014, for most reporting countries, and pipeline data for scheduled debt service payments on existing commitments to 2027.

Saudi Arabia SA: Number of Listed Domestic Companies: Total data was reported at 188.000 Unit in 2017. This records an increase from the previous number of 176.000 Unit for 2016. Saudi Arabia SA: Number of Listed Domestic Companies: Total data is updated yearly, averaging 140.500 Unit from Dec 2002 (Median) to 2017, with 16 observations. The data reached an all-time high of 188.000 Unit in 2017 and a record low of 68.000 Unit in 2002. Saudi Arabia SA: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Saudi Arabia – Table SA.World Bank: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Brazil BR: Number of Listed Domestic Companies: Total data was reported at 361.000 Unit in 2022. This records a decrease from the previous number of 381.000 Unit for 2021. Brazil BR: Number of Listed Domestic Companies: Total data is updated yearly, averaging 415.000 Unit from Dec 1979 (Median) to 2022, with 44 observations. The data reached an all-time high of 592.000 Unit in 1989 and a record low of 324.000 Unit in 2019. Brazil BR: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.;World Federation of Exchanges database.;Sum;Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Japan JP: Market Capitalization: Listed Domestic Companies data was reported at 6,222.825 USD bn in 2017. This records an increase from the previous number of 4,955.300 USD bn for 2016. Japan JP: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 3,005.697 USD bn from Dec 1975 (Median) to 2017, with 43 observations. The data reached an all-time high of 6,222.825 USD bn in 2017 and a record low of 21.530 USD bn in 1977. Japan JP: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Germany DE: Number of Listed Domestic Companies: Total data was reported at 429.000 Unit in 2022. This records a decrease from the previous number of 443.000 Unit for 2021. Germany DE: Number of Listed Domestic Companies: Total data is updated yearly, averaging 602.000 Unit from Dec 1975 (Median) to 2022, with 48 observations. The data reached an all-time high of 761.000 Unit in 2007 and a record low of 408.000 Unit in 1989. Germany DE: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.;World Federation of Exchanges database.;Sum;Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Mexico MX: Number of Listed Domestic Companies: Total data was reported at 140.000 Unit in 2018. This records a decrease from the previous number of 141.000 Unit for 2017. Mexico MX: Number of Listed Domestic Companies: Total data is updated yearly, averaging 185.000 Unit from Dec 1975 (Median) to 2018, with 43 observations. The data reached an all-time high of 410.000 Unit in 1976 and a record low of 125.000 Unit in 2009. Mexico MX: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Japan JP: Number of Listed Domestic Companies: Total data was reported at 3,598.000 Unit in 2017. This records an increase from the previous number of 3,535.000 Unit for 2016. Japan JP: Number of Listed Domestic Companies: Total data is updated yearly, averaging 1,766.000 Unit from Dec 1975 (Median) to 2017, with 43 observations. The data reached an all-time high of 3,598.000 Unit in 2017 and a record low of 1,389.000 Unit in 1978. Japan JP: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Brazil BR: Market Capitalization: Listed Domestic Companies data was reported at 794.418 USD bn in 2022. This records a decrease from the previous number of 815.877 USD bn for 2021. Brazil BR: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 815.877 USD bn from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 1,545.566 USD bn in 2010 and a record low of 126.762 USD bn in 2002. Brazil BR: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.;World Federation of Exchanges database.;Sum;Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Jamaica JM: Number of Listed Domestic Companies: Total data was reported at 71.000 Unit in 2017. This records an increase from the previous number of 64.000 Unit for 2016. Jamaica JM: Number of Listed Domestic Companies: Total data is updated yearly, averaging 49.500 Unit from Dec 1993 (Median) to 2017, with 18 observations. The data reached an all-time high of 71.000 Unit in 2017 and a record low of 38.000 Unit in 2001. Jamaica JM: Number of Listed Domestic Companies: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank: Financial Sector. Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Jamaica JM: Market Capitalization: Listed Domestic Companies: % of GDP data was reported at 34.688 % in 2011. This records an increase from the previous number of 29.446 % for 2010. Jamaica JM: Market Capitalization: Listed Domestic Companies: % of GDP data is updated yearly, averaging 28.987 % from Dec 1993 (Median) to 2011, with 12 observations. The data reached an all-time high of 62.275 % in 2002 and a record low of 21.266 % in 1995. Jamaica JM: Market Capitalization: Listed Domestic Companies: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.