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  5. DOMO vs SQueaLy

DOMO vs SQueaLy

OverviewComparisonAlternatives

Overview

DOMO
DOMO
Stacks52
Followers75
Votes0
SQueaLy
SQueaLy
Stacks0
Followers7
Votes0
GitHub Stars584
Forks47

DOMO vs SQueaLy: What are the differences?

Introduction

When comparing DOMO and SQueaLy, there are some key differences to consider. Both tools offer data management and visualization capabilities, but they have distinct features that cater to different user needs. Here are some key differences between DOMO and SQueaLy.

  1. Data Connectivity: DOMO provides integration with a wide range of data sources, including cloud applications, databases, and spreadsheets, making it easy to centralize all your data streams in one platform. On the other hand, SQueaLy focuses on seamless connectivity with SQL databases and offers robust SQL querying and reporting functionalities.

  2. Visualization Options: DOMO excels in providing a user-friendly drag-and-drop interface for creating interactive and visually appealing dashboards. It offers a variety of data visualization options such as graphs, charts, and heat maps. In contrast, SQueaLy puts more emphasis on customizable reports and dynamic SQL-based visualizations to meet specific business requirements.

  3. Data Processing Capabilities: DOMO's data processing capabilities are geared towards handling large datasets efficiently and delivering real-time insights through in-memory processing and machine learning algorithms. Meanwhile, SQueaLy prioritizes ad-hoc querying and data manipulation tasks, allowing users to perform complex SQL operations on their datasets with ease.

  4. Collaboration Tools: DOMO offers robust collaboration features, enabling team members to work together on shared datasets and dashboards in real-time. It also provides commenting and annotation tools for facilitating communication within the platform. SQueaLy, on the other hand, focuses more on individual data analysis and reporting, with limited collaborative functionalities.

  5. Scalability and Pricing: DOMO is known for its scalability, allowing businesses to handle large volumes of data and users without compromising performance. However, this scalability comes at a higher price point compared to SQueaLy, which offers more budget-friendly options for smaller organizations or individual users looking for essential data management and reporting capabilities.

  6. Customization Options: DOMO offers extensive customization options, allowing users to create personalized dashboards with tailored visuals, layouts, and branding. Users can also integrate custom scripts and applications to extend the platform's functionality. In contrast, SQueaLy focuses on providing a simpler and more streamlined user experience, with fewer customization features but a quicker setup process.

In Summary, DOMO and SQueaLy cater to different user needs, with DOMO excelling in data connectivity, visualization, and scalability, while SQueaLy focuses on SQL querying, data manipulation, and affordability.

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Detailed Comparison

DOMO
DOMO
SQueaLy
SQueaLy

Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.

SQueaLy is an open-source, self-deployable application for developers. It is a micro service for business intelligence and analytics which uses SQL queries to generate reporting APIs with fine-grained security.

Statistics
GitHub Stars
-
GitHub Stars
584
GitHub Forks
-
GitHub Forks
47
Stacks
52
Stacks
0
Followers
75
Followers
7
Votes
0
Votes
0
Integrations
Box
Box
Loggly
Loggly
Basecamp
Basecamp
HipChat
HipChat
Asana
Asana
Google BigQuery
Google BigQuery
Amazon Redshift
Amazon Redshift
Mailchimp
Mailchimp
HubSpot
HubSpot
GitHub
GitHub
Heroku
Heroku
Amazon Athena
Amazon Athena
Amazon Redshift
Amazon Redshift
MySQL
MySQL
PostgreSQL
PostgreSQL
SQLite
SQLite
Swagger UI
Swagger UI

What are some alternatives to DOMO, SQueaLy?

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.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

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