Qrvey is the #1 alternative to YellowfinBI

G2 Reviews Confirm Qrvey is Here For Your Success

Product Direction

Quality of Support

#1 Multi-Tenant Data Management

Yellowfin does not manage or store data by default but rather offers live connections to various database solutions. It uses its built-in database to store configuration and SQL queries to access each data source. Yellowfin supports standard JDBC-compliant databases, CSV uploads, and third-party APIs as data sources. 

Yellowfin also supports data transformation through a plugin, which is not enabled by default. The data transformation performs the transformation against a data source and writes to a new SQL database that needs to be configured and managed in addition to the application database.

Qrvey offers flexible data integration options to cater to various needs. It allows for both live connections to existing databases and ingesting data into its built-in data lake powered by AWS OpenSearch. This data lake approach is optimized for performance and cost-efficiency for complex analytics queries. Additionally, data is automatically normalized during ingestion to improve its suitability for multi-tenant analysis and reporting. 

Qrvey supports connections to common databases and data warehouses, and also provides an ingest API for real-time data pushing, handling JSON and semi-structured data formats like FHIR, ingesting data from cloud storage like S3 buckets, and even processing unstructured data like documents, text, and images. Qrvey includes data transformations as a built-in feature, eliminating the need for separate ETL services.

OUR TAKE

When it comes to serving SaaS companies, data management and multi-tenant security are the areas that SaaS companies often struggle with the most. Our belief is that any successful embedded analytics offering must start with data and that’s why we invest more than anyone else in the data management layer of our solution.  

#2 Qrvey Offers A Native Semantic Layer for Maximum Security

Yellowfin offers multi-tenant security through a “client organization” object structure that represents individual tenants of a SaaS platform. Every user must be assigned to a specific client org. To enable templated dashboard viewing with tenant-specific data security, Yellowfin provides two options:

1. Connecting to individual databases: Each tenant can have its own separate database, ensuring complete data isolation.
2. Using a single database with client ID parameter: If a single database is used, Yellowfin allows passing in a client ID parameter unique to each tenant. This parameter is then mapped to the relevant data within the database, ensuring each tenant only sees their own information.

For report writers, Yellowfin provides “data Views” as a way to control which data users can access when building reports. Views must be created and maintained through manual developed logic to map users to Views to ensure data security.

Additionally, it supports column-level security through “restricted columns.” However, this feature has a limitation: “Restricted columns are defined globally, meaning you cannot assign different users access to specific restricted columns within the same view. While users with restricted access won’t see these columns when creating reports, they will be visible in already created reports accessible to the user.” (source)

Qrvey simplifies user access management and data security within multi-tenant SaaS applications. Unlike traditional methods that require creating user roles and groups, Qrvey utilizes JSON Web Tokens (JWT) as its authorization mechanism. These tokens encapsulate all essential information about a user’s permissions, including their tenant association, access level (user, row, column), and even feature-specific permissions if the parent SaaS application utilizes tiered access levels. 

This eliminates the need for separate login screens or SSO methods, streamlining the user experience and reducing administrative overhead associated with managing duplicate user groups or roles. 

Additionally, Qrvey empowers users to create custom datasets at both tenant and user levels through APIs. This enables the creation of user interfaces where users can dynamically select fields and build datasets without requiring administrator intervention. 

Furthermore, Qrvey’s granular security controls grant development teams the flexibility to tailor data access precisely for individual users or tenants, surpassing limitations imposed by global security settings. 

OUR TAKE

We believe this targeted approach is particularly well-suited for the dynamic environments of multi-tenant SaaS applications. Having to manually build application layer logic to create, edit and delete users and roles in multiple systems adds to the engineering burden. We don’t want engineering teams to have to build this so including a semantic layer is an important part of Qrvey’s solution.

#3 Comparing Qrvey and Yellowfin for a Unified Embedded User Experience

Yellowfin offers two main options for embedding its analytics into a SaaS application: JavaScript API and iframes. However, iframes are generally discouraged by SaaS companies due to security concerns and limited customization capabilities. 

Yellowfin emphasizes creating a seamless user experience by ensuring a smooth transition between the main SaaS application and Yellowfin, keeping users unaware of the switch. Therefore, Yellowfin recommends deployment on a separate subdomain, creating an application that maintains a consistent user experience through:

• Matching custom header and footer: They recommend these elements should visually align with the main application and provide navigation links back to it.
• Authentication bridge: This could involve either Single Sign-On (SSO) or a custom login page to maintain consistent user authentication.

Yellowfin supports various common visualizations and offers parameters to personalize the embedded dashboard experience. Users can control the visibility of elements like filters, exports, and sharing options. Additionally, limited UI customization is possible through a custom CSS file, with documentation covering 18 CSS classes.

Qrvey prioritizes a seamless user experience within SaaS applications through 100% embeddable JavaScript-based widgets. This eliminates the security and customization limitations associated with iframes, ensuring users remain within the SaaS application at all times while interacting with Qrvey features. 

Authentication is handled through tokens generated with API calls, embedding user permissions directly into each widget upon page load. These tokens encompass comprehensive security information, including tenant and user-level data access, security-specific controls to individual charts or filters, and even row/column-level restrictions.

Qrvey further empowers customization through theme support via embed parameters, enabling easy integration with customizations such as light or dark mode themes. To power the customization, over 65 CSS classes provide granular control to the user interface, granting UX and product teams the ability to seamlessly integrate Qrvey functionalities without users noticing the presence of third-party software. 

Finally, Qrvey caters to user preferences by allowing the creation of custom dashboard templates and the editing of existing dashboards, saving them as unique user-specific versions to avoid overwriting the original template. 

OUR TAKE

This personalized approach fosters a cohesive user experience within the context of the parent SaaS application. Ultimately, embedded analytics within SaaS applications is about giving end users the freedom to create their own dashboard without the typical restrictions of a multi-tenant platform. And as third party software, SaaS end users should never know third-party software is in use.

#4 Server-Based vs. Serverless: Infrastructure Management 

Yellowfin relies on a server-based infrastructure, requiring deployment on either standalone servers or as containers. For basic dashboard functionality, a minimum of two servers are needed: one for the application server and another for the database server. Utilizing additional features like Yellowfin Signals or Stories necessitates two additional servers.

Yellowfin’s resource requirements can be challenging to estimate. While they suggest minimum specifications (8GB memory, 8 cores) for 25 concurrent users, they acknowledge the difficulty in accurately quantifying resource needs for reports demanding significant processing power. This may leads IT teams to rely on trial and error, potentially compromising the user experience if the server is misconfigured. 

Scaling also requires server clusters, incurring significant cost increases with each added server. The costs also escalate when provisioning servers needed for development, staging, and testing environments, further adding to the resource burden. 

Qrvey leverages serverless technology for a fully on-demand infrastructure, making for much more straightforward infrastructure management. Qrvey can be installed an unlimited number of times across any development environment or AWS region internationally, including GovCloud.

This model for installation and management using on-demand services creates a much more cost-effective model to meet the needs of development teams. Qrvey’s serverless approach also allows for auto-scaling of specific services as required to meet necessary performance demands.

OUR TAKE

The legacy model of installing server-based software works well for internal analytics use cases when there is a dedicated IT team to manage server clusters across many workloads. However, in a SaaS environment, DevOps needs to maintain any third-party solution so simplicity matters and so does cost-efficiency. Executive teams will look at this cost as a function of margins related to delivering software, not an internal expense so on-demand infrastructure offers the best of both worlds: security and scalability.

Information from Yellowfin version 9 as of March 1, 2024