Metabase
Tableau
Microsoft Power BI
Looker
Grafana
Redash
Domo
Qlik
Qrvey
DevicePilot
AnswerRocket
Syndigo
Amdocs CES
Yellowfin
Toucan Toco
Omniscope
Designed for external use cases where SaaS companies need to provide their customers with powerful and customizable analytics capabilities.
Qrvey is the only full stack solution that offers all the embedded visualization and self-service analytics tools along with a unified data pipeline that offers a data lake optimized for multi-tenant analytics.
Qrvey's embedded visualizations empower engineering teams to build custom experiences, along with full white labeling and CSS customization options to make Qrvey’s javascript widgets blend seamlessly into a SaaS application. ⋅⋅* Qrvey’s data-driven automation workflows enable the creation of complex workflows based on data triggers, such as conditional logic, nested functions, data write-backs with notification integrations to third party systems such as Slack. ⋅⋅* Qrvey supports natural language querying of data using generative AI to easily spot trends and outliers, augmented analysis capabilities. ⋅⋅* Qrvey also supports pixel perfect reporting to generate printable reports from the same analytics data.
Qrvey simplifies data management by providing a single data pipeline solution featuring a data lake solution that is optimized for multi-tenant analytics. This contains native data connectors and APIs to ingest data in any type from any source, including real-time data with live connections. ⋅⋅* Qrvey’s semantic layer can inherit and map security models from your multi-tenant SaaS application, saving software development teams the hassle of duplicating users and roles. ⋅⋅* Qrvey’s robust API allows you to create data delivery services and managed download functions that go beyond basic exporting.
Metabase QrveyNo features have been listed yet.
Qrvey's answer:
Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies
Qrvey's answer:
Customers choose Qrvey for the following reasons:
Qrvey's answer:
Qrvey's approach to embedded analytics is different. Qrvey combines the best of BI, data warehousing, and data visualization into a single solution built exclusively for SaaS applications.
Qrvey's key features include:
100% Embeddability - Everything is embeddable with JS based components that supports full white labeling so you can create unique analytics experiences within your SaaS application.
Data Warehouse included - Visualizations are useless without a scalable data layer built specifically for analytics use cases. Qrvey includes native multi-tenant support so your data is ready for your multi-tenant SaaS application. This includes data syncing and API support that allows for any type of data to be ingested into the Qrvey data layer.
Self-Hosted - Deployed to Your AWS Environment. Customers get ultimate control as Qrvey is deployed to their AWS environment inheriting and respecting their security policies. Your data never leaves, but it's ready for analytics now.
Based on our record, Metabase seems to be a lot more popular than Qrvey. While we know about 14 links to Metabase, 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.
I've never used Tableau, but heard a lot of hate about it. However, in my previous role, we were big fans of Metabase (https://metabase.com). You can also self-host it, which was a huge win for us. - Source: Hacker News / about 2 months ago
The solution really depends on what sort of problems you are trying to solve and who your customers are. There are a fair few low-code solutions out there for reporting and data visualisation that are great for finance and marketing teams for example. e.g. https://metabase.com/ , https://evidence.dev/ For enterprise processes I'd go with Camunda (solely based on recommendations and not first hand experience).... - Source: Hacker News / 12 months ago
Metabase | https://metabase.com | REMOTE | Full-time | Backend, Frontend, Full Stack, and DevOps engineers. - Source: Hacker News / over 1 year ago
With a few simple steps, you can deploy Metabase on Microsoft Azure using Azure Container Apps. This process works for any Docker container hosted on Docker Hub, not just Metabase, so you can try it with your containers. - Source: dev.to / over 1 year ago
Try metabase.com its built with node and uses plugins. Source: almost 2 years ago
Since you're on AWS already, check out https://qrvey.com. Source: 5 months ago
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.
Microsoft Power BI - BI visualization and reporting for desktop, web or mobile
AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.
