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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Website | apiblueprint.org |
Pricing URL | - |
Details $ | - |
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Website | qrvey.com |
Pricing URL | Official Qrvey Pricing |
Details $ | paid Free Trial |
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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, API Blueprint should be more popular than Qrvey. It has been mentiond 9 times since March 2021. 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.
As for the actual process of building the contract, what works well for me is using API Blueprint-style Markdown in a compatible tool like Apiary, which renders your content into Swagger-like documentation as you type. This way, I and others can mutually "live-scribe" the API contract as we discuss, and seeing it on-screen helps to get people on the same page (and sometimes highlight potential issues that would... Source: 11 months ago
I’m not sure a JS library qualifies as a PL. Or automation software (SoftStack). Or an API description language. Or a build system. Source: about 1 year ago
Create a Proper API Documentation The following open-source projects can help you with creating documentation for your APIs: APIBluePrint Swagger. - Source: dev.to / over 1 year ago
A common complaint about OpenAPI is that it’s difficult to learn and to read. Consequently, over the years we’ve seen many alternatives to OpenAPI, such as RAML, WADL, API Blueprint, and others. The problem with many of these alternatives is that in most cases they aren’t really more readable or easier to learn. Simpler description languages also tend to support less capabilities for documenting API features.... - Source: dev.to / almost 2 years ago
For the context of this post, only the first task is essential. In it, the team works together to define the API contract. They discuss data format, whether the API will be Rest or RPC, authentication, data compression, and other vital issues. The delivery of this task is the documentation, preferably in a standard like OpenAPI or API Blueprint (my preferred format). - Source: dev.to / over 1 year ago
Since you're on AWS already, check out https://qrvey.com. Source: 5 months ago
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