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.
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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.
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Customers choose Qrvey for the following reasons:
Based on our record, Music-Map seems to be a lot more popular than Qrvey. While we know about 20 links to Music-Map, 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.
Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago
I can't answer your question, but music-map has helped me find similar stuff to my favourite artists before. https://music-map.com. - Source: Hacker News / 5 months ago
My suggestion is you head over to music-map.com and type in the names of some artists you enjoy. The algorithm will then put up a cloud of bands/artist recommendations. Source: about 1 year ago
Have you ever fucked around on everynoise.com and music-map.com? Have fun! Source: over 1 year ago
The artists were picked either from me listening and enjoying 1 of their albums, or using the site music-map.com and finding similar artists that I already do enjoy. Source: over 1 year ago
Go to music-map and put an artist's name in the search box to find similar artists. Source: over 1 year ago
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