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  5. Periscope vs Superset

Periscope vs Superset

OverviewComparisonAlternatives

Overview

Periscope
Periscope
Stacks45
Followers94
Votes10
Superset
Superset
Stacks420
Followers1.0K
Votes45

Periscope vs Superset: What are the differences?

Key differences between Periscope and Superset

Periscope and Superset are both data visualization tools that provide interactive dashboards and data exploration capabilities, but they differ in a few key areas.

  1. Authentication: One major difference between Periscope and Superset is in their authentication systems. Periscope allows users to authenticate using various methods like Google OAuth, SAML, and JWT, ensuring secure access to user data. On the other hand, Superset primarily uses its own authentication mechanism, allowing authentication via username and password.

  2. Deployment: Another difference lies in the deployment options offered by Periscope and Superset. Periscope is a cloud-based service, meaning users can easily access and use it without having to worry about infrastructure or maintenance. Superset, however, requires manual setup and deployment on a server, which may require more technical expertise and resources.

  3. Data Sources: Periscope and Superset also differ in terms of the data sources they support. Periscope natively integrates with popular databases like PostgreSQL, MySQL, and Redshift, making it easier for users to connect to their existing data sources. On the other hand, Superset provides a broader range of data source connectors and supports a wider variety of databases, including Hive, Druid, and Presto.

  4. User Interface: The user interface of Periscope and Superset is another distinguishing factor. Periscope is known for its intuitive and user-friendly interface, making it easier for non-technical users to create and customize dashboards. Superset, while also offering a visually appealing interface, provides more advanced features and customization options that cater to users with a higher level of technical expertise.

  5. Community Support: Support and community engagement are crucial aspects when choosing a data visualization tool, and Periscope and Superset vary in this regard. Periscope has a well-established customer support team, providing prompt assistance to users when needed. In contrast, Superset has a larger open-source community and a more active contributor base, ensuring continuous development and improvement of the tool.

  6. Enterprise Features: When it comes to enterprise-level features, Periscope and Superset have different offerings. Periscope offers features like data caching, automated reports, and robust security measures, which are essential for large-scale data analysis and reporting. Superset, on the other hand, provides more advanced analytical capabilities, including complex SQL support, data slicing, and dicing, and embedding visualizations in external applications.

In summary, Periscope and Superset differ in various aspects, including authentication systems, deployment options, supported data sources, user interfaces, community support, and enterprise features. Understanding these differences can help you choose the right data visualization tool for your specific needs.

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Detailed Comparison

Periscope
Periscope
Superset
Superset

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

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.

Beautiful Visualizations;Expert Query Tools;Seamless Sharing
A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities;An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler);A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user;Deep integration with Druid allows for Caravel to stay blazing fast while slicing and dicing large, realtime datasets;
Statistics
Stacks
45
Stacks
420
Followers
94
Followers
1.0K
Votes
10
Votes
45
Pros & Cons
Pros
  • 6
    Great for learning and teaching people SQL
  • 4
    Gorgeous "share-able" and "embeddable" dashboards
Pros
  • 13
    Awesome interactive filtering
  • 9
    Free
  • 6
    Wide SQL database support
  • 6
    Shareable & editable dashboards
  • 5
    Great for data collaborating on data exploration
Cons
  • 4
    Link diff db together "Data Modeling "
  • 3
    It is difficult to install on the server
  • 3
    Ugly GUI

What are some alternatives to Periscope, Superset?

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.

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.

Looker

Looker

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.

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