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MonetDB/e, a mature embedded SQL DBMS

We introduce MonetDB/e, our new full-fledged embedded DBMS for data analytics. It encapsulates the full SQL functionality offered by MonetDB, including a rich collection of data types, triggers, schema management, and persistent stored modules.

SQL:1999 grouping combinations now supported in MonetDB

As of MonetDB Jun2020 release, we have added support for ROLLUP, CUBE and GROUPING SETS features defined by the SQL:1999 standard in the GROUP BY clause. These keywords allow one to perform multiple grouping set combinations in a single statement, containing partial and total computed results. At the same time, the GROUPING aggregate, which identifies the grouping columns used in the output, has also been implemented.

SQL:2003 merge statements now supported in MonetDB

As of the Apr2019 release of MonetDB, we have implemented the merge statement feature of the SQL:2003 standard. Merge statements allow one to conditionally insert, update and/or delete records in a target table using an input relation with a single statement.

The grammar is as follows:

merge_statement:

     [ WITH with_list ] MERGE INTO table_name [ [AS] ident ] USING input_rel [ [AS] ident ] ON search_condition merge_clause [ merge_clause ]

input_rel:

Extended SQL:2011 Window Functions in MonetDB

As of the Apr2019 release of MonetDB, we have extended MonetDB’s support for the SQL window functions to cover the majority as specified by the 2011 revision of the SQL standard. In this blogpost we describe the new functionality together with some example SQL queries to show their usage.

New analytic functions

Besides the existing RANK(), DENSE_RANK() and ROW_NUMBER() functions, we have now implemented all the remaining analytic functions listed in the SQL standard:

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