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.
Easy and scalable solution for managing and executing background tasks and microservices seamlessly in .NET applications. It allows you to schedule, queue, and process your jobs and microservices efficiently.
Designed to support distributed systems, enabling you to scale your background processes and microservices across multiple servers. With advanced features like performance monitoring, exception logging, and integration with various storage types, providing complete control and visibility over your workflow.
Provides a user-friendly web dashboard that allows you to monitor and manage your jobs and microservices from a centralized location. You can easily check the status of your tasks, troubleshoot issues, and optimize performance.
EnqueueIt is available for both .NET and Go.
The .NET packages support all EnqueueIt functionality, including the web dashboard and background jobs, which are exclusively available in the .NET package. The Go package was created as a lightweight alternative for running the EnqueueIt server, enabling the execution of microservices and seamless data synchronization between Redis and SQL databases. Additionally, the Go package supports the enqueueing and scheduling of microservices from Go, as well as the feature of reading microservice arguments.
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Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies
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dotnet and golang software engineers
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:
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It is completely opensource and free. the performance is unbeatable. it has no servers or apps limit when it come to be used in distribution systems.
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dotnet golang redis postgresql mysql sqlserver oracle
Based on our record, Qrvey seems to be more popular. It has been mentiond 1 time 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.
Since you're on AWS already, check out https://qrvey.com. Source: 6 months ago
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