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  1. Stackups
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  5. Dataform vs PyXLL

Dataform vs PyXLL

OverviewComparisonAlternatives

Overview

PyXLL
PyXLL
Stacks8
Followers104
Votes8
Dataform
Dataform
Stacks818
Followers53
Votes0
GitHub Stars934
Forks188

PyXLL vs Dataform: What are the differences?

What is PyXLL? The Python Add-In for Microsoft Excel. Integrate Python into Microsoft Excel Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python.

Works with all 3rd party and open source Python packages. No need to write any VBA!.

What is Dataform? A framework for managing SQL based data operations. Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.

PyXLL belongs to "Data Science Tools" category of the tech stack, while Dataform can be primarily classified under "Business Intelligence".

Some of the features offered by PyXLL are:

  • User Defined Functions: Write Excel worksheet functions in Python - no VBA required
  • Ribbon Customization: Give your users a rich Excel native experience
  • Macros: No need for VBA, access to the full Excel Object Model in Python

On the other hand, Dataform provides the following key features:

  • Version ontrol
  • Scheduling
  • Notifications and logging

Dataform is an open source tool with 117 GitHub stars and 11 GitHub forks. Here's a link to Dataform's open source repository on GitHub.

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Detailed Comparison

PyXLL
PyXLL
Dataform
Dataform

Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!

Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.

User Defined Functions: Write Excel worksheet functions in Python - no VBA required;Ribbon Customization: Give your users a rich Excel native experience;Macros: No need for VBA, access to the full Excel Object Model in Python;Menu Functions: Call Python functions from Excel menus, and give common tasks keyboard shortcuts;Real Time Data: Stream data to Excel in real-time using Python;Array Functions: Return tables of data to Excel that resize automatically;IntelliSense: Auto-complete worksheet functions as you type them;NumPy and Pandas Integration: Use NumPy and Pandas types in Excel
Version ontrol; Scheduling; Notifications and logging; Assertions; Web based development environment; Alerting; Incremental tables; Packages; Reusable code snippets; Unit tests; Data tests
Statistics
GitHub Stars
-
GitHub Stars
934
GitHub Forks
-
GitHub Forks
188
Stacks
8
Stacks
818
Followers
104
Followers
53
Votes
8
Votes
0
Pros & Cons
Pros
  • 5
    Fully replace VBA with Python
  • 2
    Excellent support
  • 1
    Very good performance
Cons
  • 1
    Cannot be deloyed to mac users
No community feedback yet
Integrations
Python
Python
Microsoft Excel
Microsoft Excel
Pandas
Pandas
NumPy
NumPy
Amazon Redshift
Amazon Redshift
Google BigQuery
Google BigQuery
GitHub
GitHub
JavaScript
JavaScript
PostgreSQL
PostgreSQL
Snowflake
Snowflake
Git
Git

What are some alternatives to PyXLL, Dataform?

dbForge Studio for MySQL

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

dbForge Studio for Oracle

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

dbForge Studio for PostgreSQL

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

dbForge Studio for SQL Server

dbForge Studio for SQL Server

It is a powerful IDE for SQL Server management, administration, development, data reporting and analysis. The tool will help SQL developers to manage databases, version-control database changes in popular source control systems, speed up routine tasks, as well, as to make complex database changes.

Liquibase

Liquibase

Liquibase is th leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.

Sequel Pro

Sequel Pro

Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

DBeaver

DBeaver

It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc.

dbForge SQL Complete

dbForge SQL Complete

It is an IntelliSense add-in for SQL Server Management Studio, designed to provide the fastest T-SQL query typing ever possible.

Knex.js

Knex.js

Knex.js is a "batteries included" SQL query builder for Postgres, MySQL, MariaDB, SQLite3, and Oracle designed to be flexible, portable, and fun to use. It features both traditional node style callbacks as well as a promise interface for cleaner async flow control, a stream interface, full featured query and schema builders, transaction support (with savepoints), connection pooling and standardized responses between different query clients and dialects.

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