Comparing Today's Multi-Model Databases
Multi-model databases sound simple on paper. One database, many data models, less architecture sprawl. That is the pitch. The reality is less neat. Once you look closely, "multi-model" can mean ver...

Source: DEV Community
Multi-model databases sound simple on paper. One database, many data models, less architecture sprawl. That is the pitch. The reality is less neat. Once you look closely, "multi-model" can mean very different things. Sometimes it means one engine with several models that actually work together. Sometimes it means one database plus a growing pile of attached capabilities. Sometimes it means multiple APIs over one cloud platform. Sometimes it means a strong idea that still has rough execution. So if you are evaluating the current landscape, the label alone is not enough. You need to ask harder questions. How native is the multi-model support? Does the database feel coherent, or just broad? Does it stay pleasant once the workload becomes real? Are you buying a database, or a stack of compromises with a friendly landing page? This post is my attempt to compare some of the most prominent multi-model options people talk about today: PostgreSQL + extensions SurrealDB Couchbase ArangoDB Orient