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  5. Periscope vs periscopedata

Periscope vs periscopedata

OverviewComparisonAlternatives

Overview

Periscope
Periscope
Stacks45
Followers94
Votes10
PeriscopeData
PeriscopeData
Stacks32
Followers20
Votes0

Periscope vs periscopedata: What are the differences?

Introduction:

Periscope and Periscope Data are both powerful tools for data analysis and visualization used by businesses and individuals. However, they differ in some key aspects which can impact the decision on which one to use for specific data needs.

  1. Data Sources: Periscope is primarily used for live video streaming, allowing users to broadcast and view real-time video content. On the other hand, Periscope Data is a data analysis platform that connects to various data sources such as databases, spreadsheets, and cloud services to perform advanced analytics and create visualizations.

  2. Collaboration Features: Periscope focuses on social interactions through live video streaming, providing features such as comments and likes for viewers to engage with broadcasters. In contrast, Periscope Data offers collaboration tools for teams to work together on analyzing and interpreting data, including sharing queries, dashboards, and reports.

  3. Data Visualization Capabilities: Periscope Data excels in data visualization with a wide range of charts, graphs, and interactive dashboards that can be customized to present complex data in a visually appealing way. Periscope, on the other hand, is more focused on real-time video content and lacks the advanced data visualization features of Periscope Data.

  4. Querying and Analysis: Periscope Data provides advanced querying and analysis capabilities, allowing users to write SQL queries, run sophisticated analyses, and create complex data models. Periscope, on the other hand, does not offer data querying and analysis tools and is more suitable for content creators looking to broadcast live video content.

  5. Data Security and Access Control: Periscope Data prioritizes data security and access control, offering features such as encryption, role-based permissions, and audit logs to ensure that sensitive data is protected. Periscope, being a live video streaming platform, does not focus on data security and access control in the same way as Periscope Data.

  6. Integration with Other Tools: Periscope Data is designed to integrate seamlessly with other data tools and platforms, allowing users to connect to various data sources, BI tools, and data warehouses. Periscope, as a live video streaming platform, does not offer the same level of integrations with data-related tools and focuses more on video content creation and sharing.

In Summary, Periscope is a live video streaming platform, while Periscope Data is a data analysis platform with advanced querying, visualization, and collaboration features.

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Detailed Comparison

Periscope
Periscope
PeriscopeData
PeriscopeData

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

It brings all your data together in a single platform and delivers SQL, Python, and R in one solution. Easily warehouse, analyze, visualize and share data from across your business.

Beautiful Visualizations;Expert Query Tools;Seamless Sharing
Access Your Data, When You Need It;Intuitive Drag-and-Drop Interface;Ensure Control, Consistency and Trust;
Statistics
Stacks
45
Stacks
32
Followers
94
Followers
20
Votes
10
Votes
0
Pros & Cons
Pros
  • 6
    Great for learning and teaching people SQL
  • 4
    Gorgeous "share-able" and "embeddable" dashboards
No community feedback yet
Integrations
No integrations available
Salesforce Sales Cloud
Salesforce Sales Cloud
Qubole
Qubole
Presto
Presto
Snowflake
Snowflake
Vertica
Vertica
MemSQL
MemSQL
PostgreSQL
PostgreSQL
Google BigQuery
Google BigQuery
MySQL
MySQL
Amplitude
Amplitude

What are some alternatives to Periscope, PeriscopeData?

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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