Snowplow VS Qrvey
Compare Snowplow VS Qrvey and see what are their differences
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Our Mission is to empower data teams to build a strategic data capability that delivers high-quality, complete, and relevant data across the business. Our users and customers use Snowplow for numerous use cases – from web and mobile analytics to advanced analytics and the production of AI & ML ready data, whilst maintaining data privacy compliance. Our customers reflect the diversity of use cases that Snowplow solves and includes Strava, The Wall Street Journal, CapitalOne, WeTransfer, Nordstrom, DataDog, Auto Trader, GitLab and many more.
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:
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.
Snowplow QrveyNo features have been listed yet.
Qrvey's answer:
Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies
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:
All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.
Qrvey's answer:
Customers choose Qrvey for the following reasons:
Based on our record, Snowplow should be more popular than Qrvey. It has been mentiond 10 times since March 2021. 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.
We’ve also thought about Ops :-). There’s a backend 'Collector' that stores data in Postgres, for instance to use while developing locally, or if you want to get set up quickly. But there’s also full integration with Snowplow, which works seamlessly with an existing Snowplow setup as well. - Source: dev.to / almost 2 years ago
Sure thing! Say you run an online store. Your source systems could be the inventory, orders or customer databases. You could also track click/site behavior with something like snowplow. An ERP system is essentially just a combination of what I mentioned previously. Another good example is a CRM such as Salesforce or Zendesk. Hopefully that helps! Source: about 2 years ago
Well if you have to structure and create Schema and manage Data Warehouses, you need a tool to do that, so in the background you see SnowPlow, which helps you do just that. Make the data into some kind of sensible structure so that later on business analysts can come see whats up. Want to do a quarterly report on how you performed, go to the application that goes to the data warehouse and builds your report for... Source: about 2 years ago
We also have telemetry set up on our Monosi product which is collected through Snowplow,. As with Airbyte, we chose Snowplow because of its open source offering and because of their scalable event ingestion framework. There are other open source options to consider including Jitsu and RudderStack or closed source options like Segment. Since we started building our product with just a CLI offering, we didn’t need a... - Source: dev.to / about 2 years ago
Https://matomo.org That's the only full featured open source competitor I am aware of, so it should be mentioned. https://snowplowanalytics.com/ Somewhat FOSS. There was a story there, but I don't remember the details. - Source: Hacker News / over 2 years ago
Since you're on AWS already, check out https://qrvey.com. Source: 6 months ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.
Heap - Analytics for web and iOS. Heap automatically captures every user action in your app and lets you measure it all. Clicks, taps, swipes, form submissions, page views, and more.
AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.
Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.
Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.