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Qrvey VS Google Cloud Functions

Compare Qrvey VS Google Cloud Functions and see what are their differences

Qrvey logo Qrvey

Embedded Analytics built exclusively for SaaS applications.
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Google Cloud Functions logo Google Cloud Functions

A serverless platform for building event-based microservices.
  • 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.

  • Google Cloud Functions Landing page
    Landing page //
    2023-09-25

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

Google Cloud Functions features and specs

No features have been listed yet.

Qrvey videos

Qrvey Embedded Analytics Demo

More videos:

  • Demo - Qrvey Intro Video

Google Cloud Functions videos

Google Cloud Functions: introduction to event-driven serverless compute on GCP

More videos:

  • Review - Building Serverless Applications with Google Cloud Functions (Next '17 Rewind)

Category Popularity

0-100% (relative to Qrvey and Google Cloud Functions)
Business Intelligence
100 100%
0% 0
Cloud Computing
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Cloud Hosting
0 0%
100% 100

Questions and Answers

As answered by people managing Qrvey and Google Cloud Functions.

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 Qrvey and Google Cloud Functions

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

Google Cloud Functions Reviews

We have no reviews of Google Cloud Functions yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Google Cloud Functions seems to be a lot more popular than Qrvey. While we know about 43 links to Google Cloud Functions, 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.

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: 6 months ago

Google Cloud Functions mentions (43)

  • Is Serverless Architecture Right For You?
    The first reason is that serverless architectures are inherently scalable and elastic. They automatically scale up or down based on the incoming workload without requiring manual intervention through serverless compute services like AWS Lambda, Azure Functions, or Google Cloud Functions. - Source: dev.to / 15 days ago
  • A Brief History Of Serverless
    The FaaS platform gained a lot of popularity which resulted in many competitors. There was OSS providers like OpenFaaS or Fission. There were of course the commercial versions to like Azure Functions and Google Cloud Functions. - Source: dev.to / 23 days ago
  • Increasing Your Cloud Function Development Velocity Using Dynamically Loading Python Classes
    One of the issues developers can encounter when developing in Cloud Functions is the time taken to deploy changes. You can help reduce this time by dynamically loading some of your Python classes. This allows you to make iterative changes to just the area of your application that you’re working on. - Source: dev.to / 6 months ago
  • Need some advice on API key storage
    I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights. Source: 8 months ago
  • Golden Ticket To Explore Google Cloud
    Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment. - Source: dev.to / 10 months ago
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What are some alternatives?

When comparing Qrvey and Google Cloud Functions, you can also consider the following products

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

Google App Engine - A powerful platform to build web and mobile apps that scale automatically.

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

Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.

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

AWS Lambda - Automatic, event-driven compute service