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.
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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, Lobster seems to be a lot more popular than Qrvey. While we know about 21 links to Lobster, 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 think lobster does this. "Compile time reference counting / lifetime analysis / borrow checker."[1] "Reference Counting with cycle detection at exit, 95% of reference count ops removed at compile time thanks to lifetime analysis."[1] [1] https://strlen.com/lobster/. - Source: Hacker News / 4 months ago
I think the ability to open a window and do graphical stuff is actually pretty underrated in core language functionality. There's a few game-oriented programming languages like Lobster that put windowing and graphics in the core language functionality, and I think it's pretty neat. The biggest downside is that it's a lot to bite off, because you'll probably want to have standardized API functionality for a whole... Source: about 1 year ago
There is another language, Lobster, that uses lifetime analysis like Rust, but IIUC infers lifetimes completely automatically. It looks like the idea is still experimental - I'm interested to see how it goes. Source: about 1 year ago
I'm keeping an eye on Lobster though. It fixes most of Python's problems. It's way faster, has proper static typing, the import system is sane, etc. Source: about 1 year ago
Lobster (https://strlen.com/lobster/) appears to at least do lifetime analysis to reduce refcounting. I'm not sure about automatic interior mutability. I feel like there's a keyword here that can help find other compilers with similar features. Source: about 1 year ago
Since you're on AWS already, check out https://qrvey.com. Source: 5 months ago
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