Hi Yu, I have created a roadmap website [1] and umbrella issue [2].
[1] https://paimon.apache.org/roadmap [2] https://github.com/apache/paimon/issues/6866 Best, Jingsong On Mon, Dec 22, 2025 at 1:07 PM Yong Fang <[email protected]> wrote: > > Big +1, thank Jingsong for the proposal, it marks an important step for > Paimon toward the AI Lake, and I'm very much looking forward to it. > > Best, > FangYong > > On Mon, Dec 22, 2025 at 11:03 AM Biao Liu <[email protected]> wrote: > > > Great to hear that! > > > > Thanks, > > Biao /'bɪ.aʊ/ > > > > > > > > On Thu, 18 Dec 2025 at 12:30, Yu Li <[email protected]> wrote: > > > > > Thanks for the proposal, Jingsong — big +1 from me! > > > > > > I’ve noticed there are already several active efforts underway [1][2] > > > aligned with the vision of a *unified lake format for multimodal data*. > > > Given this momentum, I think now is the right time to formalize a > > detailed > > > plan for the 2.0 release. > > > > > > One quick question: Is there a centralized place where we can track > > > detailed release progress - such as issues categorized by version, status > > > (done/in-progress/backlog) - similar to how Flink manages releases via > > JIRA > > > [3]? > > > > > > Also, would it make sense to add a dedicated **Roadmap** tab to our > > > official website, following the example of Fluss [4]? This could greatly > > > improve transparency and alignment with the community. > > > > > > Thanks. > > > > > > Best Regards, > > > Yu > > > > > > [1] > > > > > > > > https://cwiki.apache.org/confluence/display/PAIMON/PIP-35%3A+Introduce+Blob+to+store+multimodal+data > > > [2] > > > > > > > > https://cwiki.apache.org/confluence/display/PAIMON/PIP-40%3A+Introduce+a+new+Vector+data+type > > > [3] https://issues.apache.org/jira/projects/FLINK/versions/12356392 > > > [4] https://fluss.apache.org/roadmap/ > > > > > > On Thu, 18 Dec 2025 at 10:18, Chenghui Chen <[email protected]> wrote: > > > > > > > +1. Excited to see Paimon shine in the AI era! > > > > > > > > > > > > On Wed, Dec 17, 2025 at 10:28 PM Mehul Batra <[email protected] > > > > > > > wrote: > > > > > > > > > +1. > > > > > Looking forward to it. > > > > > > > > > > Best regards, > > > > > Mehul > > > > > > > > > > On Wed, Dec 17, 2025 at 5:14 PM yuxia <[email protected]> > > > > wrote: > > > > > > > > > > > +1. > > > > > > Looking forward to it. > > > > > > > > > > > > Best regards, > > > > > > Yuxia > > > > > > > > > > > > ----- 原始邮件 ----- > > > > > > 发件人: "Blue Umi" <[email protected]> > > > > > > 收件人: "dev" <[email protected]> > > > > > > 发送时间: 星期三, 2025年 12 月 17日 下午 2:17:43 > > > > > > 主题: [SPAM]Re: [DISCUSS] Apache Paimon 2.0 Version planning > > > > > > > > > > > > +1, I can't wait to see the wide application of paimon in the field > > > of > > > > > AI. > > > > > > > > > > > > On Wed, Dec 17, 2025 at 12:29 PM 王刚 <[email protected]> wrote: > > > > > > > > > > > > > +1, looking forward to the optimizations of Paimon in AI > > scenarios. > > > > > > > > > > > > > > wj wang <[email protected]> 于2025年12月17日周三 10:33写道： > > > > > > > > > > > > > > > +1, very pleased to see Paimon's progress in AI. > > > > > > > > > > > > > > > > On Wed, Dec 17, 2025 at 9:04 AM Yunfeng Zhou > > > > > > > > <[email protected]> wrote: > > > > > > > > > > > > > > > > > > Thanks for the proposal. It would definitely boost Paimon’s > > > > > > development > > > > > > > > in the next era for AI. > > > > > > > > > > > > > > > > > > Best, > > > > > > > > > Yunfeng > > > > > > > > > > > > > > > > > > > 2025年12月16日 16:45，Jingsong Li <[email protected]> 写道： > > > > > > > > > > > > > > > > > > > > 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 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
