# resources
Many systems that started out rejecting the RM with much fanfare (think NoSQL) now expose a SQL-like interface for RM databases. Such systems are now on a path to convergence with RDBMSs.
Do not ignore the out-of-box experience. One of the salient selling points of many non-relational DBMSs is a better “out-of-box” experience than RDBMSs. Most SQL systems require one first to create a database and then define their tables before they can load data. This is why data scientists use Python notebooks to analyze data files quickly. Every DBMS should, therefore, make it easy to perform in situ processing of local and cloudstorage files. DuckDB’s rising popularity is partly due to its ability to do this well.
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from the summary, looks like the only DB type that will not be displaced by RDBMSs are indeed Array workloads for scientific data. good to see that SQL:2023 added so many interesting features, wondering when those will be adopted by e.g. PostgreSQL
thanks for sharing @Nok Lam Chan!
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^Andy (one of the author) has THE BEST online database courses on Youtube
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More recent work showed how SQL/PGQ in DuckDB outperforms a leading graph DBMS by up to 10x
👀 https://www.cidrdb.org/cidr2023/papers/p66-wolde.pdf
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The YouTube channel mentioned by Nok: https://www.youtube.com/@CMUDatabaseGroup/playlists
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