Vortex TSDB (Time Series Database) is a highly scalable and flexible time series data storage solution built on Java and Spring Boot. Designed to efficiently store and analyze time series data with fine granularity (down to 1-minute intervals), Vortex TSDB provides robust features for real-time monitoring, analytics, and large-scale data management. With its extensible architecture and integration capabilities, Vortex TSDB is a powerful tool for applications requiring precision and high...
Vortex TSDB supports fine-grained data storage with a granularity of 1-minute intervals, making it suitable for real-time analytics and precision monitoring. Key data types supported include:
- Double
- Long
- Decimal
These data types enable precise measurements and calculations tailored to diverse application needs.
The database provides a comprehensive set of built-in statistical operations, enabling deep insights into time series data:
- Maximum and Minimum Values: Identify peaks and troughs in your data.
- Average Values: Calculate trends and patterns over time.
- Variance: Measure data variability for predictive analytics.
- Baseline Comparisons: Evaluate deviations from expected values.
These capabilities make Vortex TSDB a strong choice for applications requiring rich data analysis.
- Redis-Based Storage: The current implementation leverages Redis for fast, in-memory storage, ensuring low-latency read and write operations.
- Future-Ready Architecture: Plans to support additional storage backends like MySQL or other databases, providing developers with flexibility to choose the optimal storage solution for their use case.
- Built on Netty NIO: Ensures efficient, non-blocking IO for high-throughput communication.
- Horizontal Scalability: Add more nodes to scale out the system seamlessly.
- Fault Tolerance: Designed for high availability to ensure consistent service delivery in distributed environments.
Vortex TSDB includes a benchmark testing UI to evaluate performance metrics such as throughput, latency, and resource utilization. This makes it easier for users to test, analyze, and optimize the database in their specific environments.
- Java 17+
- Redis 7.x (for storage backend)
- Maven (for building the project)
git clone https://github.com/paganini2008/vortex.git
cd vortexmvn clean install
java -jar target/vortex-tsdb-web.jar- Path:
/tsd/push - Method:
POST - Description: Push time series data to the server.
- Example Request:
http://localhost:55610/tsd/push?t=long&c=car&d=speed&v=44
| Parameter Name | Type | Required | Description | Example Value |
|---|---|---|---|---|
| t | String | Yes | Data type (long/decimal/double) | long |
| c | String | Yes | Category (e.g., device category or system module) | car |
| d | String | Yes | Dimension (e.g., metric name) | speed |
| v | String | Yes | Value (supports numeric string) | 44 |
- Path:
/tsd/retrieve - Method:
GET - Description: Retrieve stored time series data.
- Example Request:
http://localhost:57741/tsd/retrieve?t=long&c=car&d=speed
| Parameter Name | Type | Required | Description | Example Value |
|---|---|---|---|---|
| t | String | Yes | Data type (long/decimal/double) | long |
| c | String | Yes | Category (e.g., device category or system module) | car |
| d | String | Yes | Dimension (e.g., metric name) | speed |
| z | String | No | Time zone (default: Australia/Sydney) | Asia/Shanghai |
Navigate to http://localhost:8080/tsd/metric to access the benchmark testing UI and explore the database capabilities.
For detailed documentation, API reference, and advanced configuration, visit the Official Documentation.
We welcome contributions! Check out the Contributing Guide for more information on how to get involved.
This project is licensed under the MIT License. See the LICENSE file for details.
Vortex TSDB combines precision, scalability, and extensibility to deliver a cutting-edge time series database solution. Whether for real-time monitoring, predictive analytics, or large-scale data management, Vortex TSDB provides the tools and flexibility you need to succeed.