dbt

dbt

dbt Labs
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About

AutoIt v3 is a freeware BASIC-like scripting language designed for automating the Windows GUI and general scripting. It uses a combination of simulated keystrokes, mouse movement, and window/control manipulation in order to automate tasks in a way not possible or reliable with other languages. We looked at many editors to see which one was the most useful editor for AutoIt. We found SciTE and saw its potential and wrote a customized Lexer for the syntax highlighting and syntax folding and created a special installer called SciTE4AutoIt3. AutoIt was initially designed for PC "roll out" situations to reliably automate and configure thousands of PCs. Over time it has become a powerful language that supports complex expressions, user functions, loops and everything else that veteran scripters would expect.AutoIt is also very small, self-contained and will run on all versions of Windows out-of-the-box with no annoying "runtimes" required.

About

SQL is a domain-specific programming language used for accessing, managing, and manipulating relational databases and relational database management systems.

About

dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.

About

pywinauto is a set of python modules to automate the Microsoft Windows GUI. At its simplest it allows you to send mouse and keyboard actions to Windows dialogs and controls. pywinauto can be installed with pip and conda. Python is a great programming language, but there are no automation tools that were Pythonic (very few libraries were implemented in Python). The very first necessary thing is to determine which accessibility technology (pywinauto’s backend) could be used for your application. First, you should start your application or connect to an existing app instance. It can be done with an application object. It’s a core concept for the high-level pywinauto API. You are able to describe any window or control approximately or in more detail even if it doesn’t exist yet or is already closed. Window specification also keeps the information about the matching/search algorithms that will be used to get a real window or control.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers seeking a tool for automating the Windows GUI and their general scripting processes

Audience

Developers and database admins

Audience

SQL users looking for a ETL solution to engineer data transformations

Audience

Indoviduals in need of a tool to send mouse and keyboard actions to Windows dialogs and controls

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

$100 per user/ month
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 3.7 / 5
ease 5.0 / 5
features 4.7 / 5
design 4.0 / 5
support 2.3 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

AutoIt
United States
www.autoitscript.com/site/

Company Information

SQL
Founded: 1974
sourceforge.net/software/product/SQL/

Company Information

dbt Labs
Founded: 2016
United States
www.getdbt.com

Company Information

pywinauto
United States
pywinauto.readthedocs.io/en/latest/

Alternatives

Alternatives

dbt

dbt

dbt Labs

Alternatives

Alternatives

PowerShell

PowerShell

Microsoft
Racket

Racket

Racket Language
Automation Workshop

Automation Workshop

Febooti, Ltd.

Categories

Categories

Categories

dbt powers the transformation layer of modern data pipelines. Once data has been ingested into a warehouse or lakehouse, dbt enables teams to clean, model, and document it so it’s ready for analytics and AI. With dbt, teams can: - Transform raw data at scale with SQL and Jinja. - Orchestrate pipelines with built-in dependency management and scheduling. - Ensure trust with automated testing and continuous integration. - Visualize lineage across models and columns for faster impact analysis. By embedding software engineering practices into pipeline development, dbt helps data teams build reliable, production-grade pipelines to accelerate time to insight, and deliver AI-ready data.

dbt brings rigor and scalability to data preparation by enabling teams to clean, transform, and structure raw data directly in the warehouse. Instead of siloed spreadsheets or manual workflows, dbt uses SQL and software engineering best practices to make data preparation reliable, repeatable, and collaborative. With dbt, teams can: - Clean and standardize data with reusable, version-controlled models. - Apply business logic consistently across all datasets. - Validate outputs through automated tests before data is exposed to analysts. - Document and share context so every prepared dataset comes with lineage and definitions. By treating data preparation as code, dbt ensures that prepared datasets aren’t just quick fixes — they’re trusted, governed, and production-ready assets that scale with the business.

ETL

dbt modernizes the “T” in ETL: Transformation. Instead of relying on legacy pipelines or black-box transformations, dbt empowers data teams to build, test, and document transformations directly inside the data warehouse or lakehouse. With dbt, teams can: - Transform raw data into analytics-ready models using SQL and Jinja. - Ensure reliability with built-in testing, version control, and CI/CD. - Standardize workflows across teams with reusable models and shared documentation. - Leverage modern platforms like Snowflake, Databricks, BigQuery, and Redshift for scalable transformation. By focusing on the transformation layer, dbt helps organizations shorten pipeline development cycles, reduce data debt, and deliver trusted insights faster — complementing ingestion and loading tools in a modern ELT stack.

Categories

Big Data Features

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Lineage Features

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Preparation Features

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

ETL Features

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

Integrations

Accops HySecure
Brakeman
Cohere
Death By Captcha
DeepSeek Coder
DeepSeek R2
Digital Twin Studio
GPT-5 mini
Gigasheet
Hanabi.rest
Haystack
OpenAI o3-mini-high
PandaAI
Paradime
Quandis Business Objects
Raptool Designer
Select Star
UltraEdit
XTDB
Zenlytic

Integrations

Accops HySecure
Brakeman
Cohere
Death By Captcha
DeepSeek Coder
DeepSeek R2
Digital Twin Studio
GPT-5 mini
Gigasheet
Hanabi.rest
Haystack
OpenAI o3-mini-high
PandaAI
Paradime
Quandis Business Objects
Raptool Designer
Select Star
UltraEdit
XTDB
Zenlytic

Integrations

Accops HySecure
Brakeman
Cohere
Death By Captcha
DeepSeek Coder
DeepSeek R2
Digital Twin Studio
GPT-5 mini
Gigasheet
Hanabi.rest
Haystack
OpenAI o3-mini-high
PandaAI
Paradime
Quandis Business Objects
Raptool Designer
Select Star
UltraEdit
XTDB
Zenlytic

Integrations

Accops HySecure
Brakeman
Cohere
Death By Captcha
DeepSeek Coder
DeepSeek R2
Digital Twin Studio
GPT-5 mini
Gigasheet
Hanabi.rest
Haystack
OpenAI o3-mini-high
PandaAI
Paradime
Quandis Business Objects
Raptool Designer
Select Star
UltraEdit
XTDB
Zenlytic
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