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What is HeidiSQL?

HeidiSQL is a free software tool designed for ease of use, enabling users to view and modify data as well as manage structures on systems utilizing MariaDB, MySQL, or Microsoft SQL databases. Created by Ansgar in 2002, HeidiSQL has become one of the leading applications for working with MariaDB and MySQL. This open-source program is accessible to all and allows for the simultaneous connection of multiple servers within a single interface. It supports not only MariaDB, MySQL, and MS SQL but also offers connectivity through command line, SSH tunnels, or SSL settings. Users can perform a wide range of actions, including editing tables, views, stored procedures, triggers, and scheduled events, as well as creating elegant SQL exports that can be compressed or copied directly to the clipboard. Moreover, exporting data can be done seamlessly from one server or database to another, and the tool offers functionality for managing user privileges, importing text files, and exporting table rows in various formats such as CSV, HTML, XML, SQL, LaTeX, Wiki Markup, and PHP Array. With a user-friendly grid interface, HeidiSQL facilitates effortless browsing and editing of table data, making database management intuitive and efficient. Overall, the versatility and robust features of HeidiSQL make it an indispensable tool for database administrators and developers alike.

What is Advanced ETL Processor?

Advanced ETL Processor is a flexible data processing solution that helps organizations connect, transform, and automate information flows between different systems. The software works with many data sources, including spreadsheets, text files, structured formats, APIs, and enterprise databases such as MySQL, PostgreSQL, SQL Server, Oracle, and MariaDB. Its visual configuration interface allows users to design workflows that clean, validate, reshape, and transfer data without complex programming. Advanced ETL Processor is commonly used for system integration, data migration, reporting pipelines, and analytics preparation. Automation and scheduling features ensure that data processes run reliably, reducing manual effort and improving data consistency across business applications. The platform is suitable for both small projects and large-scale enterprise data operations, providing a practical way to manage data movement and transformation in modern IT environments.

Media

Media

Integrations Supported

Firebird
MariaDB
MySQL
PostgreSQL
SQL Server
SQLite
Brightpearl
ChatGPT
Gemini
Google Sheets
Greenplum
IBM Informix
InterBase
Microsoft Access
Microsoft Excel
Oracle Database
ProxySQL
Qlik Cloud Analytics
Salesforce
Sesame Software

Integrations Supported

Firebird
MariaDB
MySQL
PostgreSQL
SQL Server
SQLite
Brightpearl
ChatGPT
Gemini
Google Sheets
Greenplum
IBM Informix
InterBase
Microsoft Access
Microsoft Excel
Oracle Database
ProxySQL
Qlik Cloud Analytics
Salesforce
Sesame Software

API Availability

Has API

API Availability

Has API

Pricing Information

$0
Free Trial Offered?
Free Version

Pricing Information

$690 per user per year
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

HeidiSQL

Date Founded

2002

Company Location

Germany

Company Website

www.heidisql.com

Company Facts

Organization Name

DB Software Laboratory

Date Founded

2008

Company Location

United Kingdom

Company Website

www.etl-tools.com

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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