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, Prometheus seems to be a lot more popular than Qrvey. While we know about 230 links to Prometheus, 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.
The open source projects Fastly uses and the foundations we partner with are vital to Fastly’s mission and success. Here's an unscientific list of projects and organizations supported by the Linux Foundation that we use and love include: The Linux Kernel, Kubernetes, containerd, eBPF, Falco, OpenAPI Initiative, ESLint, Express, Fastify, Lodash, Mocha, Node.js, Prometheus, Jenkins, OpenTelemetry, Envoy, etcd, Helm,... - Source: dev.to / 15 days ago
Prometheus is the best-known time-series database engine. It has many use cases, but in the context of Kubernetes, it's a great way to store and query metrics that provide observability for your cluster and its workloads. You can receive alerts when metrics change, such as a Node CPU usage spike or a Pod failure, and integrate with tools like Grafana to visualize your values on dashboards. - Source: dev.to / 21 days ago
Implement health checks and monitoring to ensure the availability and performance of your microservices. Use tools like Prometheus, Grafana, or NestJS built-in health checks. - Source: dev.to / 28 days ago
Kubernetes Documentation: https://kubernetes.io/docs/home/ Kubernetes Tutorials: https://kubernetes.io/docs/tutorials/ Kubernetes Community: https://kubernetes.io/community/ Prometheus: https://prometheus.io/ Grafana: https://grafana.com/ Elasticsearch: https://www.elastic.co/elasticsearch/ Kibana: https://www.elastic.co/kibana Helm: https://helm.sh/ Prometheus Helm Chart:... - Source: dev.to / about 2 months ago
Monitoring tools and performance profiling methods are invaluable in identifying performance bottlenecks. These tools provide real-time insights into API behavior, enabling developers to spot inefficiencies and potential issues. There's a range of monitoring tools, including platforms like New Relic, Datadog, and Prometheus that offer extensive performance metrics like response times, error rates, and resource... - Source: dev.to / about 2 months ago
Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago
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