Open Source Time Series Database 2025-2033 Analysis: Trends, Competitor Dynamics, and Growth Opportunities

Key Insights

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.

Open Source Time Series Database Trends

The open source time series database market is experiencing a surge in popularity, with a projected market size of over $1.2 billion by 2025. This growth is driven by the increasing volume and complexity of time series data, coupled with the need for real-time analysis and insights.

Time series data is a sequence of data points collected over time, which can be used to track trends, identify anomalies, and make predictions. Open source time series databases provide a cost-effective and flexible solution for storing, processing, and analyzing this data.

Driving Forces: What's Propelling the Open Source Time Series Database

The growth of the open source time series database market is driven by several key factors:

• Increasing volume and complexity of time series data: The Internet of Things (IoT) and other data-generating technologies are producing vast amounts of time series data. This data is often unstructured and complex, requiring specialized databases for efficient storage and processing.
• Need for real-time analysis and insights: Businesses need to be able to analyze time series data in real-time to make informed decisions. Open source time series databases provide the performance and scalability required for this type of analysis.
• Cost-effectiveness and flexibility: Open source time series databases are typically free to use and can be customized to meet the specific needs of an organization. This makes them an attractive option for businesses of all sizes.

Challenges and Restraints in Open Source Time Series Database

Despite the growing popularity of open source time series databases, there are also some challenges and restraints that need to be considered:

• Lack of standardization: There is a lack of standardization in the open source time series database market, which can make it difficult to compare and choose between different products.
• Security concerns: Open source software can be vulnerable to security breaches, so it is important to take appropriate security measures when using open source time series databases.
• Technical expertise required: Using open source time series databases requires some technical expertise, which can be a barrier for some organizations.

Key Region or Country & Segment to Dominate the Market

The United States is the largest market for open source time series databases, followed by Europe and Asia-Pacific. The cloud-based segment is expected to dominate the market, as more businesses move to cloud-based infrastructure.

The Internet of Things (IoT) industry is the largest application segment for open source time series databases, followed by the financial industry and the telecommunications industry.

Growth Catalysts in Open Source Time Series Database Industry

Several factors are expected to contribute to the growth of the open source time series database market in the coming years:

• Increasing adoption of IoT and other data-generating technologies: The IoT is expected to connect billions of devices by 2025, which will generate vast amounts of time series data. This data will need to be stored, processed, and analyzed in order to extract valuable insights.
• Rising demand for real-time analytics: Businesses are increasingly looking to use real-time analytics to make informed decisions. Open source time series databases can provide the performance and scalability required for this type of analysis.
• Growing awareness of the benefits of open source software: Open source software is becoming increasingly popular as businesses recognize its cost-effectiveness, flexibility, and security advantages.

Leading Players in the Open Source Time Series Database

Some of the leading players in the open source time series database market include:

• InfluxData
• Timescale
• Prometheus
• OpenTSDB
• VictoriaMetrics
• QuestDB

Significant Developments in Open Source Time Series Database Sector

There have been several significant developments in the open source time series database sector in recent years:

• InfluxData has released InfluxDB 2.0, a major update to its popular time series database. InfluxDB 2.0 offers improved performance, scalability, and security.
• Timescale has released TimescaleDB 2.0, a major update to its time series database. TimescaleDB 2.0 offers improved performance, scalability, and support for PostgreSQL.
• Prometheus has released Prometheus 2.0, a major update to its time series database. Prometheus 2.0 offers improved performance, scalability, and support for Kubernetes.

Comprehensive Coverage Open Source Time Series Database Report

This report provides a comprehensive overview of the open source time series database market. The report includes detailed market size and forecast data, as well as in-depth analysis of the market trends, drivers, and challenges. The report also provides profiles of the leading players in the market.

Open Source Time Series Database Segmentation

• 1. Type
  • 1.1. Cloud-Based
  • 1.2. On-Premises
• 2. Application
  • 2.1. Internet of Things Industry
  • 2.2. Financial Industry
  • 2.3. Telecommunication Industry
  • 2.4. Others

Open Source Time Series Database Segmentation By Geography

• 1. North America
  • 1.1. United States
  • 1.2. Canada
  • 1.3. Mexico
• 2. South America
  • 2.1. Brazil
  • 2.2. Argentina
  • 2.3. Rest of South America
• 3. Europe
  • 3.1. United Kingdom
  • 3.2. Germany
  • 3.3. France
  • 3.4. Italy
  • 3.5. Spain
  • 3.6. Russia
  • 3.7. Benelux
  • 3.8. Nordics
  • 3.9. Rest of Europe
• 4. Middle East & Africa
  • 4.1. Turkey
  • 4.2. Israel
  • 4.3. GCC
  • 4.4. North Africa
  • 4.5. South Africa
  • 4.6. Rest of Middle East & Africa
• 5. Asia Pacific
  • 5.1. China
  • 5.2. India
  • 5.3. Japan
  • 5.4. South Korea
  • 5.5. ASEAN
  • 5.6. Oceania
  • 5.7. Rest of Asia Pacific