IginX (Intelligent/IoT Engine X) is an open-source clustering system for multi-dimensional scaling of standalone time series databases through generalized sharding. It is already deployed in real applications such as train monitoring and intelligent factories.
IginX features in the following aspects:
- High Scalability
IginX is a stateless service. It can be easily scaled out or scaled up. You can expand the system's routing and processing capacity by simply adding new IginX instances. Vertically scale-up the computing resources for a single instance can also expand the system's capacity.
- Smooth Elasticity
With IginX you can even split and merge slices in multiple dimensions as your needs grow, with an atomic cutover step that takes only a few seconds. Applications will rarely notice any performance degradation in the process, thanks to the carefully tailored design of metadata and reconfiguration procedure.
- Transparent Data Distribution
By encapsulating data slice orchestration logic, IginX allows application code and time series data queries to remain agnostic to the distribution of data onto multiple slices. Users need only care about the data access logic of their applications by IginX.
- Integration with Heterogeneous Databases
IginX provides a common abstraction of time series databases. As long as an implementation of the abstraction is provided and configured for a time series database, it can be managed by and accessed through IginX. Within a running cluster of IginX, heterogenous time series databases can coexist and serve the same set of applications.
- Flexible Slicing and Replication
IginX allows for flexible data slicing and replication to suit the skewed application workloads, which commonly exist in real world. This can be achieved through an implementation of the IPolicy interface.
For more details, please refer to our technological posts on time series management under this link. However, IginX is still under active development and yet to be mature. You are highly encourage to try it and share us with your experience.
Quick starts in Chinese (A complete version——完整版部署说明文档):
- Use IginX in one shot：单机版IginX一键运行使用
- Use IginX by compiling sources：基于代码编译使用IginX
- Use IginX by docker：基于 Docker 使用IginX
- Deploy an IginX Cluster：IginX集群版部署
Or, please refer to our User manual in Chinese. User manual in English is still being written, but you might contact Yuqing Zhu for IginX in case of any question or problem.
If you are interested in time series data management by large, you are highly welcomed to join our IginX workshop in every month's last Friday afternoon at 2pm by Tencent online meeting. Please contact the IginX-maintainers for information about the Tencent online meeting.
Contributions are welcomed and greatly appreciated. To report a problem the best way to get attention is to create a GitHub issue. To report a security vulnerability, please email IginX-maintainers.
Unless otherwise noted, the IginX source files are distributed under the Apache Version 2.0 license found in the LICENSE file.