Evidence.dev
Blazer
Chartbrew
Metabase
Observable
Kanaries RATH
Tableau
RATH
Qrvey
DevicePilot
AnswerRocket
Syndigo
Yellowfin
Amdocs CES
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.
Evidence.dev QrveyNo features have been listed yet.
No Evidence.dev videos yet. You could help us improve this page by suggesting one.
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, Evidence.dev seems to be a lot more popular than Qrvey. While we know about 13 links to Evidence.dev, 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.
We use echarts at https://evidence.dev and have been quite happy with it. We do a lot of embedded analytics and it's worked well for us. - Source: Hacker News / 12 days ago
It’s interesting to me how far you have pushed the SQL language in this framework, such that it truly is “SQL only”. The challenge as I see it with enabling analysts to build websites is that you need to build abstractions to get from familiar (SQL, yaml) - the language of analytics, to new (HTML, CSS, JS) - the language of the web browser As one of the maintainers of Evidence ( - Source: Hacker News / 2 months ago
Dataclips was my first experiences writing SQL. Writing code was a markedly better DX that building dashboards in Tableau, which is why I'm now working on https://evidence.dev - a SSG for creating data from SQL and markdown Previous HN discussions:. - Source: Hacker News / 2 months ago
I'm one of the founders of Evidence (https://evidence.dev) - would be great to hear about your experience. Reaching out now! - Source: Hacker News / 2 months ago
Full fledged BI tools like Superset and Metabase are amazing for their intended use cases. But they may be an overkill if your primary use case is to infrequently build semi-interactive reports for non-technical end-users and your use cases are are mostly covered by standard graphs & tables. Esp. So if you are familiar with SQL and have access to the underlying data source. Two nifty utilities I have found to be... - Source: Hacker News / 2 months ago
Since you're on AWS already, check out https://qrvey.com. Source: 5 months ago
Blazer - Open source business intelligence tool.
DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.
Chartbrew - Create interactive dashboards and reports from your databases, APIs, and 3rd party services. Supporting MySQL, Postgres, MongoDB, Firestore, Customer.io, and more. Chartbrew is 100% open source and can be self-hosted for free.
AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.
Metabase - Metabase is the easy, open source way for everyone in your company to ask questions and learn from...
Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.