>I believe that future data platforms will adopt an all-in-one approach, offering OLTP, OLAP, as well as support for other hybrid workloads such as vector, grap

>I believe that future data platforms will adopt an all-in-one approach, offering OLTP, OLAP, as well as support for other hybrid workloads such as vector, graph, and time series It's already available and open source by the nice folks from MIT and they even wrote a book on it [1],[2]. You can use it to develop modern datahub for data engineering and analytics [3],[4]. [1] D4M: Dynamic Distributed Dimensional Data Model: https://d4m.mit.edu/ https://d4m.mit.edu/ [2] Mathematics of Big Data: Spreadsheets, Databases, Matrices, and Graphs: https://mitpress.mit.edu/9780262038393/mathematics-of-big-data/ https://mitpress.mit.edu/9780262038393/mathematics-of-big-da... [3] Technical Report: Developing a Working Data Hub: https://arxiv.org/abs/2004.00190 https://arxiv.org/abs/2004.00190 [4] Collaborative data analytics with DataHub: https://dspace.mit.edu/handle/1721.1/100937 https://dspace.mit.edu/handle/1721.1/100937