2 beautiful tests transformed in the dbSQWare team for Lucas HIBOS and Emmy PAYAN!

After a 6-month internship in business with us, they are now in Bachelor 3 – Sales & Negotiation at Euridis Business School and starting today, their first week of work-study, on the company side.
We are delighted to have them back after a 3-week break and to extend this great adventure!

We also wish good luck to Julien CORNAND, who has just completed his B3 apprenticeship year – Systems and Network Administrator at CESI, following his graduation.

Congratulations to all !

Unique in its kind, the dbSQWare software allows its users to manage all of their DBMS in a completely homogeneous manner, despite their heterogeneity.

Its installation takes place in 4 essential phases:
🔎  the definition and study of the architecture in place,
💻  the configuration and customization of dbSQWare according to the environment,
🚀  software deployment,
🤝  and finally, the passage of knowledge on its daily use.

Installing dbSQWare means choosing reliability, agility and peace of mind, through global management and vision of your databases.

A statistic (on a table, a column / a set of columns or on an index) provides information on:
– the table (number of lines, average size of a line, number of blocks/page, density),
– the distribution of values ​​for the column(s) (number of distinct values, number of duplicates, existence of null values, histogram of distribution of values),
– the composition of the index (depth, number of blocks, cluster ratio).

These statistics are used by the database optimizer to study the different execution plans that can be used for a query.
The optimizer (based on costs / CBO) chooses the best execution plan (least expensive) from the data calculated from these statistics on, in particular, the number of rows and blocks of data to be shuffled at each stage of these plans (access strategies).

Statistics are essential for the proper calculation of query execution plans. It is therefore essential that they are up to date to take into account changes to the data and therefore to the indexes, columns and tables.
Thanks to update statistics, the optimizer has reliable data to choose the best performing execution plan to serve data to applications.