Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Experience a comprehensive and robust tool for managing, administering, and developing databases specifically for PostgreSQL. Effortlessly browse, create, modify, duplicate, rename, and remove various schema elements such as tables, views, functions, and triggers with remarkable ease. Streamline your data modeling efforts by establishing tables and relationships with just a few clicks of your mouse. You can also print diagrams or save them in multiple graphical file formats for further use. Utilize an expansive array of tools to browse, edit, print, sort, group, and filter your data, including master-detail views for enhanced organization. Develop graphical diagrams and OLAP cubes to visualize your data more effectively. Take advantage of a feature-rich SQL Editor equipped with code completion, code folding, and formatted SQL, or construct your queries visually for added convenience. Data export capabilities extend to 20 of the most commonly used file formats, while you can also import data from sources such as Excel, CSV, and XML. Ensure the safety and security of your server by utilizing the powerful tools offered by PostgreSQL Maestro. Moreover, effortlessly split denormalized tables, generate DML procedures or updatable views, and verify nullable columns, all with just a few simple clicks for a more efficient database management experience.
Description
In QDeFuZZiner software, the fundamental unit is referred to as a project, which encompasses the definitions of two source datasets for import and analysis, known as the "left dataset" and "right dataset." Each project not only includes these datasets but also a variable number of solutions that detail the methodology for conducting fuzzy match analysis. Upon creation, every project is assigned a distinct project tag, which is subsequently appended to the names of the corresponding input tables during the raw data import process. This tagging system guarantees that the imported tables maintain uniqueness through association with their respective project names. Furthermore, during the import phase and later when generating and executing solutions, QDeFuZZiner establishes various indexes on the PostgreSQL database, thereby enhancing the efficiency of fuzzy data matching procedures. The datasets themselves can be sourced from spreadsheet formats such as .xlsx, .xls, .ods, or from CSV (comma separated values) flat files, which are uploaded to the server database, leading to the creation, indexing, and processing of the associated left and right database tables. This structured approach not only simplifies data management but also streamlines the analysis process, making it easier for users to derive insights from their datasets.
API Access
Has API
No
API Access
Has API
No
Integrations
PostgreSQL
Yes
Digna
Yes
IBM Cloud Databases
Yes
Microsoft 365
Yes
Microsoft Excel
Yes
MySQL
Yes
Oracle Database
Yes
PHP
Yes
XML
Yes
Integrations
PostgreSQL
Yes
Digna
No
IBM Cloud Databases
No
Microsoft 365
No
Microsoft Excel
No
MySQL
No
Oracle Database
No
PHP
No
XML
No
Pricing Details
$99 one-time payment
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
SQL Maestro
Founded
2002
Country
United States
Website
www.sqlmaestro.com/products/postgresql/maestro/
Vendor Details
Company Name
QDeFuZZiner
Website
zmatasoft.wixsite.com/qdefuzziner/qdefuzziner-software-features