MySQL Workbench enables the developers to perform all kind of data modelling require for complicated ER models, forward and reverse engineering. In addition to data modelling the MySql Workbench also provides SQL development, build SQL queries, manage MySQL servers other admin tools for database backup and recovery configuring servers, users audit data, monitoring, database health and more… In simple words, the developers or administrators can visually design, generate, manage and model the databases directly from the interface of the MySQL Workbench. The Sakila example databases were lifted from jOOQ, which in turn owe their heritage to earlier work on Sakila.MySQL Workbench is a tool that used a very rich Graphical user interface to provide a comprised visual platform for developers and database architectures or Database administrators.Additionally, sq incorporates modified versions of:.See go.mod for a list of third-party packages.Jsonl JSON Lines: LF-delimited JSON objects false Jsona JSON Array: LF-delimited JSON arrays false See the tutorial for further details, but given an Excel source and a CSV source you can do: There are massive optimizations to be made, but none have been implemented yet. Thus, performance is abysmal for larger tables. Note: The current mechanism for these joins is highly naive: sq copies the joined table from each source to a “scratch database” (SQLite by default), and then performs the JOIN using the scratch database’s SQL interface. That is, you can join an Excel worksheet with a CSV file, or Postgres table, etc. Sq has rudimentary support for cross-source joins. Person 7 table - 4 uid, username, email, address_id INTEGER, TEXT, TEXT, INTEGER $ sq -insert 7 rows into sq inspect ROWS TYPE SIZE NUM COLS COL NAMES COL TYPES Sq inspect is your friend (output abbreviated):

Sakila demo database