Overview

Mode

Stacks126

Followers227

Votes17

Looker

Stacks636

Followers656

Votes9

Looker vs Mode: What are the differences?

Introduction: Looker and Mode are both powerful data analysis tools that enable businesses to visualize and analyze their data. Despite having similar goals, there are some key differences between Looker and Mode.

Data Exploration Capabilities: Looker emphasizes on providing an interactive and user-friendly interface for data exploration. It offers features like auto-suggested visualizations, data filters, and drill-down capabilities, enabling users to explore and analyze data easily. On the other hand, Mode focuses on providing a versatile SQL editor, allowing users to perform complex queries, write custom SQL code, and create advanced data transformations and calculations.
Collaboration and Sharing: Looker puts a strong emphasis on collaboration and sharing within teams. It provides built-in tools for creating and sharing saved visualizations, dashboards, and reports with colleagues, enabling seamless collaboration and knowledge sharing. In contrast, Mode provides a collaborative environment through its collaborative SQL editor, where users can collaborate in real-time on SQL queries and share their analyses with others.
Embedding and Customization: Looker offers extensive embedding capabilities, allowing users to embed Looker-developed reports and dashboards directly into third-party websites and applications. It provides SDKs and APIs for customizing the look and feel of embedded content and integrating with other systems. In comparison, while Mode also offers embedding options, it provides less flexibility in terms of customization and integration compared to Looker.
Data Modeling and Transformation: Looker provides a robust data modeling layer, enabling users to transform and structure their data for analysis. It offers a visual interface for building data models, defining relationships and aggregations, and creating business logic. Mode, on the other hand, primarily focuses on SQL-based data analysis, allowing users to directly manipulate and transform data using SQL queries without the need for complex data modeling.
Data Source Connectivity: Looker supports a wide range of data sources, including popular databases, cloud storage services, and data warehouses. It offers connectors and pre-built integrations for seamless data connectivity and syncing. Mode also supports various data sources, but its list of supported data sources is comparatively smaller than Looker's, limiting the options for data connectivity.
Pricing and Licensing: Looker follows a subscription-based pricing model, where pricing is based on factors such as the number of users, data volume, and additional features required. It offers different pricing tiers based on the organization's needs. On the other hand, Mode offers both free and paid plans, with the free plan having limitations on features and functionalities. The paid plans offer additional features and more flexibility in terms of data volume and collaboration.

In summary, Looker emphasizes on data exploration, collaboration, and embedding capabilities, while Mode focuses on SQL-based analysis, data modeling, and customization. Looker offers a wider range of data source connectivity options and follows a subscription-based pricing model, whereas Mode has a more limited set of data sources and offers a free plan with paid options.

Advice on Mode, Looker

Mohan

CEO at UPJAUNT

Nov 10, 2020

Needs adviceon

Firebase

Google BigQuery

Data Studio

We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.

497k views497k

Comments

Lyndon

Sep 11, 2022

Decided

Looking for an environment to help with exploring behavioral data, and creating dashboards for an account-based marketing approach. As we dug into options, I learned of Looker Actions, which enabled us to send the results of queries to the Segment Track and Identify api's. This enabled me to easily send CRM data to marketing tools integrated via the Segment CDP. At the time, no other BI environment provided a similar capability to automatically activate data, rather than just visualize it.

27.4k views27.4k

Comments

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k

Comments

Detailed Comparison

Mode	Looker
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.	We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.
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.	Zero-lag access to data;No limits;Personalized setup and support;No uploading, warehousing, or indexing;Deploy anywhere;Works in any browser, anywhere;Personalized access points
Statistics
Stacks 126	Stacks 636
Followers 227	Followers 656
Votes 17	Votes 9
Pros & Cons
Pros 4 Empowering for SQL-first analysts 3 Easy report building 3 Collaborative query building 2 Awesome online and chat support 2 In-app customer chat support	Pros 4 Real time in app customer chat support 4 GitHub integration 1 Reduces the barrier of entry to utilizing data Cons 3 Price
Integrations
Apache Hive Microsoft Azure Google BigQuery Apache Impala Amazon Redshift PostgreSQL Segment MySQL Microsoft SQL Server	No integrations available

What are some alternatives to Mode, Looker?

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'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: 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

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

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

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 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

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.