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  1. Stackups
  2. Application & Data
  3. Databases
  4. Database Tools
  5. Dataform vs DbSchema

Dataform vs DbSchema

OverviewComparisonAlternatives

Overview

DbSchema
DbSchema
Stacks11
Followers26
Votes10
Dataform
Dataform
Stacks818
Followers53
Votes0
GitHub Stars934
Forks188

Dataform vs DbSchema: What are the differences?

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; DbSchema: Database design and administration GUI. It helps you design, document and manage databases without having to be a SQL pro. Easily design new tables, generate HTML5 documentation, explore and edit the database data, compare and synchronize the schema over multiple databases, edit and execute SQL, generate random data.

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

Some of the features offered by Dataform are:

  • Version ontrol
  • Scheduling
  • Notifications and logging

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

  • ER diagrams
  • Reverse engineer schema from database
  • Relational data browser

Dataform is an open source tool with 191 GitHub stars and 25 GitHub forks. Here's a link to Dataform's open source repository on GitHub.

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Detailed Comparison

DbSchema
DbSchema
Dataform
Dataform

DbSchema is the perfect tool for designing and managing any SQL, NoSQL, or Cloud Database. Using the intuitive GUI you can edit & browse complex databases with just a few clicks.

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.

Reverse Engineer the Schema (works for MongoDB); Interactive Layouts; Relational Data Browse; Visual Query Builder; Schema Synchronization; HTML5 Documentation; Random Data Generator; Data Loader; Forms & Reports; SQL Editor with auto-completion; Work Offline;
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
11
Stacks
818
Followers
26
Followers
53
Votes
10
Votes
0
Pros & Cons
Pros
  • 2
    MongoDb diagrams
  • 1
    Mysql Data Explorer
  • 1
    Intuitive interface, complete design using diagrams
  • 1
    All databases included: PostgreSQL, MariaDb, Redshift
  • 1
    MongoDb documentation
No community feedback yet
Integrations
Cassandra
Cassandra
MongoDB
MongoDB
MySQL
MySQL
Google BigQuery
Google BigQuery
PostgreSQL
PostgreSQL
MSSQL
MSSQL
MariaDB
MariaDB
HSQLDB
HSQLDB
Apache Ignite
Apache Ignite
Microsoft Azure
Microsoft Azure
Amazon Redshift
Amazon Redshift
Google BigQuery
Google BigQuery
GitHub
GitHub
JavaScript
JavaScript
PostgreSQL
PostgreSQL
Snowflake
Snowflake
Git
Git

What are some alternatives to DbSchema, 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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