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.
Qrvey's answer:
Customers choose Qrvey for the following reasons:
Based on our record, Go Programming Language seems to be a lot more popular than Qrvey. While we know about 293 links to Go Programming Language, 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.
In today's fast-paced software development landscape, efficient workflows and clear responsibilities between development and design teams are crucial. One effective way to streamline these workflows is by automating component generation from design tools like Figma to code using powerful programming languages like Golang. This article will explore the process of converting Figma components to code, focusing on the... - Source: dev.to / 11 days ago
Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention. - Source: dev.to / 2 months ago
Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited... - Source: dev.to / about 2 months ago
Make sure you have Go installed https://go.dev/. - Source: dev.to / 2 months ago
I've been writing a lot about Go and gRPC lately:. - Source: dev.to / 3 months ago
Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago
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