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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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, Azure Functions should be more popular than Qrvey. It has been mentiond 3 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.
This article shows with the simple example how to manage Java-based serverless APIs build with Azure functions. It uses azure-functions plugin to integrate Apache APISIX API Gateway with Azure Serverless Function that invokes the HTTP trigger functions and return the response from Azure Cloud. - Source: dev.to / over 1 year ago
GitHub Actions for Azure: This GitHub Action allows developers to automate tasks on the Microsoft Azure platform. With this action, developers can easily integrate Azure services into their workflows, such as Azure Functions, App Services, and Kubernetes. This can help streamline DevOps workflows by automating tasks such as deployment, testing, and scaling on the Azure platform. - Source: dev.to / over 1 year ago
NoOps is best suited for born-in-the-cloud environments that leverage PaaS and serverless solutions. Microservices and API-based application architectures fit the bill perfectly, as they offer fine-grained modularity along with automation. Leading cloud service providers like AWS, Azure, and GCP have a laser focus on providing more services and capabilities in PaaS and serverless, which would help accelerate the... - Source: dev.to / almost 3 years ago
Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago
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