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  5. Interana vs Periscope

Interana vs Periscope

OverviewComparisonAlternatives

Overview

Periscope
Periscope
Stacks45
Followers94
Votes10
Interana
Interana
Stacks5
Followers13
Votes0

Interana vs Periscope: What are the differences?

Interana: Analyze Billions of Events in Seconds. Interana is a solution for exploring, monitoring, and sharing data about your product, customers, and business. Run it on premises or in the cloud, share with tens to thousands of co-workers, and scale from millions to trillions of events; Periscope: Periscope plugs directly into your database and lets you run, save and share analyses over billions of data rows in seconds. Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

Interana and Periscope belong to "Business Intelligence" category of the tech stack.

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Detailed Comparison

Periscope
Periscope
Interana
Interana

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

Interana is a solution for exploring, monitoring, and sharing data about your product, customers, and business. Run it on premises or in the cloud, share with tens to thousands of co-workers, and scale from millions to trillions of events.

Beautiful Visualizations;Expert Query Tools;Seamless Sharing
-
Statistics
Stacks
45
Stacks
5
Followers
94
Followers
13
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
Kafka
Kafka
Amazon S3
Amazon S3
Azure Storage
Azure Storage
Segment
Segment

What are some alternatives to Periscope, Interana?

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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