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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
API Access
Has API
Integrations
PostgreSQL
Digna
IBM Cloud Databases
Microsoft 365
Microsoft Excel
MySQL
Oracle Database
PHP
XML
Integrations
PostgreSQL
Digna
IBM Cloud Databases
Microsoft 365
Microsoft Excel
MySQL
Oracle Database
PHP
XML
Pricing Details
$99 one-time payment
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
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