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  5. DOMO vs Mode

DOMO vs Mode

OverviewDecisionsComparisonAlternatives

Overview

Mode
Mode
Stacks125
Followers227
Votes17
DOMO
DOMO
Stacks52
Followers75
Votes0

DOMO vs Mode: What are the differences?

Introduction

In this article, we will compare and highlight the key differences between DOMO and Mode, two popular data analytics platforms.

  1. Data Visualization Capabilities: DOMO is primarily focused on providing powerful data visualization features. It offers a wide range of pre-built visualizations and dashboards that can be easily customized to present data in an engaging and intuitive manner. On the other hand, Mode is more focused on providing advanced analytics and reporting capabilities, with a limited set of built-in visualizations.

  2. Collaborative Data Science: Mode excels in fostering collaboration among data scientists and analysts. It allows users to work on the same notebook simultaneously, annotate and discuss code, and easily share insights with others. In contrast, DOMO is more geared towards business users and provides a collaborative environment for data exploration, visualization, and reporting, but with limited capabilities for code sharing and collaboration among technical users.

  3. Data Modeling and Analysis: Mode offers robust modeling and analysis functionalities, including support for SQL queries, Python, and R notebooks. It allows users to manipulate, transform, and analyze data using a wide range of tools and libraries. On the other hand, while DOMO offers some data analysis capabilities, it is primarily designed for data visualization and reporting, with limited support for advanced data modeling and analysis tasks.

  4. Data Integration: DOMO provides seamless integrations with a wide range of data sources and systems, making it easier to connect, collect, and transform data from different sources into a unified view. Mode, on the other hand, provides connectors to popular databases, warehouses, and APIs, but may require more manual configuration and customization for data integration tasks.

  5. Enterprise-grade Security and Governance: Mode provides advanced security controls, including enterprise-level Single Sign-On (SSO), two-factor authentication, and role-based permissions, making it suitable for organizations that prioritize security and governance. DOMO also offers security features, but Mode provides more comprehensive control and compliance options for enterprise deployments.

  6. Deployment Options: DOMO is a cloud-based platform, offering a fully managed service in the cloud. It provides the advantage of easy scalability, seamless upgrades, and reduced IT infrastructure requirements. In contrast, Mode offers both cloud and on-premises deployment options, allowing organizations to choose the deployment model that best suits their needs and compliance requirements.

In Summary, DOMO is primarily focused on data visualization and reporting, with strong integration capabilities, while Mode excels in collaborative data science with advanced modeling and analysis functionalities.

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Advice on Mode, DOMO

Wei
Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k
Comments

Detailed Comparison

Mode
Mode
DOMO
DOMO

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.

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.

Write, save, and share SQL queries with other analysts in your company; Empower non-technical folks to update queries on their own; Run queries on a schedule, create lists of related reports, and explore a project's history as it changes over time; Build reports using standard charting or create completely customer, interactive visuals with HTML, CSS, and Javascript;Database connectors for MySQL, Postgres, Redshift, Vertica, Hive, Heroku, Segment, BigQuery, Impala; Mode also offers SQL School (sqlschool.modeanalytics.com), a free, interactive SQL tutorial and the Mode Playbook.
-
Statistics
Stacks
125
Stacks
52
Followers
227
Followers
75
Votes
17
Votes
0
Pros & Cons
Pros
  • 4
    Empowering for SQL-first analysts
  • 3
    Collaborative query building
  • 3
    Easy report building
  • 2
    Integrated IDE with SQL + Python for analysis
  • 2
    In-app customer chat support
No community feedback yet
Integrations
Apache Hive
Apache Hive
Microsoft Azure
Microsoft Azure
Google BigQuery
Google BigQuery
Apache Impala
Apache Impala
Amazon Redshift
Amazon Redshift
PostgreSQL
PostgreSQL
Segment
Segment
MySQL
MySQL
Microsoft SQL Server
Microsoft SQL Server
Box
Box
Loggly
Loggly
Basecamp
Basecamp
HipChat
HipChat
Asana
Asana
Google BigQuery
Google BigQuery
Amazon Redshift
Amazon Redshift
Mailchimp
Mailchimp
HubSpot
HubSpot
GitHub
GitHub

What are some alternatives to Mode, DOMO?

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.

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.

Periscope

Periscope

Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

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