Hi everyone, Apache Paimon, as a high-performance data lake format, has achieved significant results in the field of structured data processing. With the deepening of AI application scenarios, the demand for fusion analysis of multimodal data (such as text, images, audio, video, etc.) is increasing day by day. We have invested a lot of development work in cross modal retrieval, unified storage, and efficient analysis.
We plan to launch version 2.0 development, focusing on breaking through multimodal data support and creating a more powerful data lake solution. Core objective: - Unified Storage for structure & multimodal & vector. - Efficient Search for data and vectors. - Python ecosystem. Core features: 1. Data Evolution mode. 2. Blob Store. 3. Vector Store. 4. Python SDK & Ray Supports 5. Global Index framework. 6. Global Vector Index. 7. Global Invert Index. What do you think? Best, Jingsong
