The reason we can't replace SQL is that it is the lingua franca between many client tools and data sources. From programming languages, to Analytics tools, to ETL tools to bulk data transfer tools, everything knows how to define SQL queries. On the datastorage side, almost everything is standardizing on SQL as its API: RDBMSes, but also NoSQL storage (etc, hadoop + hive, etc), data virtualization layers (denodo, aws athena, steam pipe).
You can't change this by providing a better query language in one of the datasource products, or by providing a better ORM. Because of the network effects it will be very hard to come up with something better that is universally adopted. Many have tried though but it's always limited to a small stack: MDX, DAX, Linq, Dplyr, Graphql, etc.
There may be opportunities to replace SQL as soon as we need something that moves away from relational algebra. Currently you see al lot of adoption on graph storage and graph query languages in the Data Fabric space, as users need to build queries reasoning about relationships between different datasets in the enterprise.
The other reason Data Fabrics could offer an opportunity here is that they're basically adding an layer of abstraction between all data sources and data consumers, and they the possibility to translate SQL into something else, e.g. graphql.
You can't change this by providing a better query language in one of the datasource products, or by providing a better ORM. Because of the network effects it will be very hard to come up with something better that is universally adopted. Many have tried though but it's always limited to a small stack: MDX, DAX, Linq, Dplyr, Graphql, etc.
There may be opportunities to replace SQL as soon as we need something that moves away from relational algebra. Currently you see al lot of adoption on graph storage and graph query languages in the Data Fabric space, as users need to build queries reasoning about relationships between different datasets in the enterprise.
The other reason Data Fabrics could offer an opportunity here is that they're basically adding an layer of abstraction between all data sources and data consumers, and they the possibility to translate SQL into something else, e.g. graphql.