Software Alternatives, Accelerators & Startups

Qrvey VS AWS Elastic Load Balancing

Compare Qrvey VS AWS Elastic Load Balancing and see what are their differences

Qrvey logo Qrvey

Embedded Analytics built exclusively for SaaS applications.
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AWS Elastic Load Balancing logo AWS Elastic Load Balancing

Amazon ELB automatically distributes incoming application traffic across multiple Amazon EC2 instances in the cloud.
  • Qrvey Landing page
    Landing page //
    2023-11-21
  • Qrvey
    Image date //
    2024-05-20
  • Qrvey
    Image date //
    2024-05-20

Qrvey is the only purpose-built solution for embedded analytics

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:

  • Elasticsearch as the analytics engine
  • A unified data pipeline for ingestion and transformation
  • A complete semantic layer for simple user and data security integration

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.

  • AWS Elastic Load Balancing Landing page
    Landing page //
    2023-04-27

Qrvey features and specs

  • Embedded Dashboards: Yes
  • Embedded Dashboard Builders: Yes
  • Embedded Single Charts/Metrics: Yes
  • Embedded Single Chart/Metric Builder: Yes
  • Data Warehouse: Yes
  • ETL: Yes
  • Alerts and Automation: Yes
  • Embedded Pixel-Perfect Reports: Yes
  • Native Multi-Tenant Data Security: Yes
  • Tenant Specific Content Deployment: Yes
  • Prebuilt Data Connectors (Redshift, PostgreSQL, Snowflake, etc): Yes

AWS Elastic Load Balancing features and specs

No features have been listed yet.

Qrvey videos

Qrvey Embedded Analytics Demo

More videos:

  • Demo - Qrvey Intro Video

AWS Elastic Load Balancing videos

No AWS Elastic Load Balancing videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Qrvey and AWS Elastic Load Balancing)
Data Dashboard
100 100%
0% 0
Web Servers
0 0%
100% 100
Business Intelligence
100 100%
0% 0
Web And Application Servers

Questions and Answers

As answered by people managing Qrvey and AWS Elastic Load Balancing.

How would you describe your primary audience?

Qrvey's answer

Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies

What makes your product unique?

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:

  • Everything is a JS embed, no iFrames
  • Dashboards and builders
  • Dataset creation for individual users
  • No-code workflow automation
  • Full white-labeling and CSS support

All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.

Why should a person choose your product over its competitors?

Qrvey's answer

Customers choose Qrvey for the following reasons:

  • In-house engineering teams spend less time developing analytics features
  • Infrastructure costs are significantly less
  • Engineering teams get JS embeds and a richer API suite than anyone else
  • Fully customizable to blend in seamlessly with the parent SaaS application

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Qrvey and AWS Elastic Load Balancing

Qrvey Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Qrvey is an embedded analytics platform used for SaaS data, analytics, and automation technologies. You can deploy it right into your pre-existing AWS account in order to visualize your entire data pipeline. Their start-ups package includes specialized support for pre-launch or early-launch companies, like quick installation and launch, serverless analytics scalability,...
Source: theqalead.com
Top 5 Embedded Analytics Tools for Amazon Redshift (Plus 1 Bonus Option)
Qrvey is an embedded analytics and automation tool designed specifically for SaaS applications. It connects directly to AWS and offers an all-in-one platform that includes data collections, analysis, visualizations, automation, and more.
Source: yurbi.com

AWS Elastic Load Balancing Reviews

We have no reviews of AWS Elastic Load Balancing yet.
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Social recommendations and mentions

Based on our record, AWS Elastic Load Balancing seems to be a lot more popular than Qrvey. While we know about 22 links to AWS Elastic Load Balancing, 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.

Qrvey mentions (1)

  • Looking for an embedded report builder solution that doesn't require giving a third-party access to the data
    Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago

AWS Elastic Load Balancing mentions (22)

  • A Ride Through Optimising Legacy Spring Boot Services For High Throughput
    Use load balancers and distribute load accordingly to your redundant spring boot services. - Source: dev.to / 3 months ago
  • DevSecOps with AWS- Ephemeral Environments – Creating test Environments On-Demand - Part 1
    • Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that helps you easily deploy, manage, and scale containerized applications. • AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. AWS Fargate is compatible with both Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic... - Source: dev.to / 9 months ago
  • AWS wastes money.
    Elite Dangerous. With proper setup, AWS works great. And I am sure there are hundreds or even thousands of games using them, but not all are willing to share that information. Source: about 1 year ago
  • Fortifying Your Three-Tier Application: Proactive Measures for Strengthening Your Application Security
    Terraform templates can be used to automate the deployment and configuration of the Presentation Tier components. This Terraform code snippet can be used to deploy an AWS Elastic Load Balancer (ELB):. - Source: dev.to / about 1 year ago
  • What is something that you don't understand, but at this point are too embarrassed to ask?
    Assuming you already have two LBs (as above), most services will offer auto scaling of some description to handle this (e.g., https://aws.amazon.com/elasticloadbalancing/). Source: about 1 year ago
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What are some alternatives?

When comparing Qrvey and AWS Elastic Load Balancing, you can also consider the following products

DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.

nginx - A high performance free open source web server powering busiest sites on the Internet.

Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.

Traefik - Load Balancer / Reverse Proxy

AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.

Azure Traffic Manager - Microsoft Azure Traffic Manager allows you to control the distribution of user traffic for service endpoints in different datacenters.