It is exciting to hear the new directions, most of which focus on the integration with the AI eco-systems.
I personally do not participate in many AI-related works. Nevertheless, I feel it interesting to apply TsFile in as many areas as possible. If some detailed user cases can be provided, I am more than happy to join the brainstorm of evolving TsFile to the next generation. Best, Tian Jiang ---- Replied Message ---- | From | Caiyin Yang<[email protected]> | | Date | 12/31/2025 15:48 | | To | <[email protected]> | | Subject | Re: Future Directions of Apache TsFile | Hi Jialin, I strongly support the integration with Hugging Face Datasets. The primary bottleneck in Time-Series AI today is not a lack of data, but the lack of standardized, high-performance Data IO. Native integration would transform TsFile into a foundational infrastructure for the TS community, rather than just another file format. From our experience developing the Sundial model, such a bridge would make sharing datasets like TimeBench seamless. More importantly, it unlocks massive industrial IoT data from IoTDB directly into AI training pipelines. Let's make TsFile the "first-class citizen" for Time-Series in the AI ecosystem. I'm eager to help define the technical requirements! Best, Caiyin Yang On 2025/12/30 12:37:20 Jialin Qiao wrote: Hi all, With the release of TsFile 2.2.0, the project now offers multi-language SDKs (Python, Java, C++, C), enabling seamless data storage for terminal devices, real-time edge-side processing, and cloud-based data analysis. Its support for table models further simplifies data analysis and model training in Python. As AI continues to gain momentum, TsFile can serve as a foundational format for building industrial time-series datasets in the AI era. Here are some potential work we could do 1. Deeper alignment with the Python ecosystem, such as Pandas & DataFrame. 2. Integration with HuggingFace Datasets. 3. Viewer of a TsFile. 4. Converter between other formats(such as Parquet, CSV, HDF5) and TsFile. Welcome further ideas to advance the TsFile community :-) Thanks, Jialin Qiao
