Software Alternatives, Accelerators & Startups

Ruffle VS Qrvey

Compare Ruffle VS Qrvey and see what are their differences

Ruffle logo Ruffle

An open source Flash player

Qrvey logo Qrvey

Embedded Analytics built exclusively for SaaS applications.
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  • Ruffle Landing page
    Landing page //
    2023-05-25
  • Qrvey Landing page
    Landing page //
    2023-11-21
  • Qrvey
    Image date //
    2024-05-20
  • Qrvey
    Image date //
    2024-05-20

Qrvey is the only purpose-built solution for embedded analytics

Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application.

Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less.

Qrvey’s multi-tenant data lake includes:

  • Elasticsearch as the analytics engine
  • A unified data pipeline for ingestion and transformation
  • A complete semantic layer for simple user and data security integration

Qrvey’s embedded visualizations support everything from: - Standard dashboards and templates - Self-service reporting - User-level personalization - Individual dataset creation - Data-driven workflow automation

Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users.

The result: Less time and money on analytics.

Ruffle features and specs

No features have been listed yet.

Qrvey features and specs

  • Embedded Dashboards: Yes
  • Embedded Dashboard Builders: Yes
  • Embedded Single Charts/Metrics: Yes
  • Embedded Single Chart/Metric Builder: Yes
  • Data Warehouse: Yes
  • ETL: Yes
  • Alerts and Automation: Yes
  • Embedded Pixel-Perfect Reports: Yes
  • Native Multi-Tenant Data Security: Yes
  • Tenant Specific Content Deployment: Yes
  • Prebuilt Data Connectors (Redshift, PostgreSQL, Snowflake, etc): Yes

Ruffle videos

*NEW* Amazon Ruffle Lehenga Unboxing & Review | Trendy Lehenga | Latest Designer Lehenga

More videos:

  • Review - Amazon Ruffle Saree Review 909 rs | Festive Unboxing Day 2 | Perkymegs Hindi
  • Review - Swisholic - Designer Ruffle Saree Unboxing, Review & Try On | My Birthday Gift | Nikki's Passion

Qrvey videos

Qrvey Embedded Analytics Demo

More videos:

  • Demo - Qrvey Intro Video

Category Popularity

0-100% (relative to Ruffle and Qrvey)
Online Services
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Product Presentation
100 100%
0% 0
Business Intelligence
0 0%
100% 100

Questions and Answers

As answered by people managing Ruffle and Qrvey.

How would you describe your primary audience?

Qrvey's answer:

Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies

What makes your product unique?

Qrvey's answer:

Qrvey takes a different approach to embedded analytics. Instead of focusing almost completely on the front end, we know that any analytics function starts with data.

Qrvey includes a full-featured data lake powered by Elasticsearch, not a basic relational caching layer. Furthermore, by including a data lake, the cost to scale out is much less than traditional data warehouses.

For the user-facing components of the platform, Qrvey offers more embedded components and APIs to personalize the experience beyond static dashboards. Qrvey offers:

  • Everything is a JS embed, no iFrames
  • Dashboards and builders
  • Dataset creation for individual users
  • No-code workflow automation
  • Full white-labeling and CSS support

All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.

Why should a person choose your product over its competitors?

Qrvey's answer:

Customers choose Qrvey for the following reasons:

  • In-house engineering teams spend less time developing analytics features
  • Infrastructure costs are significantly less
  • Engineering teams get JS embeds and a richer API suite than anyone else
  • Fully customizable to blend in seamlessly with the parent SaaS application

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Ruffle and Qrvey

Ruffle Reviews

We have no reviews of Ruffle yet.
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Qrvey Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Qrvey is an embedded analytics platform used for SaaS data, analytics, and automation technologies. You can deploy it right into your pre-existing AWS account in order to visualize your entire data pipeline. Their start-ups package includes specialized support for pre-launch or early-launch companies, like quick installation and launch, serverless analytics scalability,...
Source: theqalead.com
Top 5 Embedded Analytics Tools for Amazon Redshift (Plus 1 Bonus Option)
Qrvey is an embedded analytics and automation tool designed specifically for SaaS applications. It connects directly to AWS and offers an all-in-one platform that includes data collections, analysis, visualizations, automation, and more.
Source: yurbi.com

Social recommendations and mentions

Based on our record, Ruffle seems to be a lot more popular than Qrvey. While we know about 230 links to Ruffle, we've tracked only 1 mention of Qrvey. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Ruffle mentions (230)

  • Revive old flash games using ruffle and trystero
    Some of you may know ruffle (https://ruffle.rs). - Source: Hacker News / 3 days ago
  • Orisinal: Morning Sunshine (recovered old flash games)
    The memories… I often wondered what would happen to those wonderful Orisinal mini games after Flash's death, without actually checking out the site. Would Ferry Halim find the time to port them to "HTML5"? Would they just… disappear forever? It turns out that they know run in Ruffle[1], a Rust/WASM based Flash Player emulator I've never heard of (or forgotten about). The handful of them that I have tested work... - Source: Hacker News / 3 months ago
  • WebAssembly Playground
    shrug It finds its uses. It's just not that overstated. Sandspiel is quite popular and is built using WASM: https://sandspiel.club/ Google Earth - https://blog.chromium.org/2019/06/webassembly-brings-google-earth-to-more.html Ruffle (the "make Flash run safely" tool) - https://ruffle.rs/ Ableton's Learning Synths - https://learningsynths.ableton.com/ etc etc. It's just hard to tell when something is using... - Source: Hacker News / 4 months ago
  • Amon Tobin – Foley Room site (2007)
    I was amazed that the site still runs, apparently still using the same engine. But it seems that it was a flash site (of course), and archive.org seems to replace Flash Player with "Ruffle" [1]. Either that, or someone of Tobin's team replaced Flash with Ruffle >= 2019. [1] https://ruffle.rs/. - Source: Hacker News / 5 months ago
  • It's the offseason, so it's time to face the most lethal bullpen ever assembled. Let's play Winnie the Pooh's Home Run Derby!
    It is Flash! You're playing it with the free and open-source Flash clone Ruffle. Source: 6 months ago
View more

Qrvey mentions (1)

  • Looking for an embedded report builder solution that doesn't require giving a third-party access to the data
    Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago

What are some alternatives?

When comparing Ruffle and Qrvey, you can also consider the following products

BlueMaxima's Flashpoint - the webgame preservation project.

DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.

Lightspark - The Lightspark project

Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.

CheerpX for Flash - its adobe flash player in webassembly

AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.